Answer Capsule
Profound is a strong fit for enterprise buyers who need AI citation source intelligence, competitor citation benchmarking, and citation-architecture mapping, but it is a measurement and workflow platform rather than a fully outsourced GEO agency. Five of seven platforms named Profound during the ranking stage (openai, anthropic, google, grok, perplexity), and it finished first overall with an average listed rank of 3.4 and a best rank of 1. Its strongest reason to consider it is page-level citation tracking tied to competitor benchmarking and crawler analytics. Its main limitation is that execution — content production, schema repair, outreach, and PR — is not bundled, and enterprise pricing is quote-only.
Research Snapshot
| Field | Finding |
|---|---|
| Platform mentions in ranking stage | 5 of 7 platforms named Profound (openai, anthropic, google, grok, perplexity) |
| Share of included platform responses | 71.4% (5 of 7) |
| Average listed rank | 3.4 |
| Best listed rank | 1 |
| Relevant product/model/plan | Profound Enterprise, centered on Answer Engine Insights, Pages, Agent Analytics, citation analytics, and Profound Agents |
| Overall use-case fit | Strong (openai, anthropic, google, grok); Good (deepseek, perplexity); Mixed (kimi) |
| Research date | 2026-09-17 |
Why Profound Qualified for This Study
Questions This Section Answers
- Is Profound a good choice for AI Citation Partners for Source Intelligence, Strategy, and Execution?
- Which platforms ranked Profound first for AI citation source intelligence, and why?
Profound qualified because it was named by five of the seven platforms during ranking discovery and finished first overall, with three platforms placing it at rank 1 (openai, deepseek, perplexity) and two placing it at rank 7 (google, grok). The platforms that ranked it first cited its citation-tracking depth, competitor benchmarking, and crawler analytics as the reasons it belongs in this category [1].
The strongest qualification signal is that Profound's product surface maps directly onto the buyer's stated needs: identifying which domains and pages influence AI answers, measuring own and competitor citations, mapping category citation architecture, and connecting citations to recommendations [1]. Independent reviews also describe it as an enterprise-grade AEO tool with Answer Engine Insights, AI bot crawl analysis, Prompt Volumes, and Agents [6].
The weaker qualification signal is that Profound is primarily a measurement and analytics platform, not a content-production or execution service [6]. Buyers who need done-for-you GEO execution should treat Profound as one component of a coordinated program rather than a single-vendor solution.
The Product, Model, Plan, or Service Most Relevant to AI Citation Partners for Source Intelligence, Strategy, and Execution
Questions This Section Answers
- Which Profound plan should a buyer choose for enterprise AI citation source intelligence across multiple engines?
- Does Profound Enterprise include Answer Engine Insights, Agent Analytics, and Profound Agents in one package?
The relevant configuration for this use case is Profound Enterprise, centered on Answer Engine Insights, Pages, Agent Analytics, citation analytics, and Profound Agents [8]. Answer Engine Insights is the module that tracks brand and competitor citations, visibility score, visibility rank, citation share, share of voice, sentiment, average position, and prompt-level gaps [11].
Pages combines owned-page citation data with content scores and page health, and optionally layers in Agent Analytics bot and referral data [13]. Agent Analytics tracks AI crawler behavior — GPTBot, PerplexityBot, ClaudeBot, GoogleOther — and can connect to CDNs including Cloudflare, Akamai, Fastly, AWS, Google Cloud, Netlify, and WordPress [15]. Profound Agents is a no-code workflow automation layer that generates content briefs, research lists, and AEO content drafts from citation data [17].
The Profound Index adds category-level rankings, topic clusters, co-citation, co-mention, mention position, and citation-share views based on real-user conversation data, according to Profound [18]. Public materials describe different plan-level and product-level platform coverage, so exact availability for the recommended enterprise configuration is unclear and should be confirmed in the quote [8].
What the AI Platforms Agreed About
Questions This Section Answers
- What do AI platforms agree Profound does best for AI citation source intelligence?
- Is Profound consistently recommended for mapping citation architecture and competitor citations?
The platforms agreed on several points. First, Profound tracks which specific URLs and domains are cited in AI-generated answers, and it surfaces citation share, source categories, and competitor citations [20]. Second, it supports competitive benchmarking — showing prompts where competitors are cited but the buyer is not [21]. Third, it classifies cited sources into categories such as Owned, Competition, Earned Media, PR Wire, Social, and Institution, which supports authority-gap and earned-media prioritization [24].
Fourth, the platforms agreed that Profound is enterprise-oriented, with SSO/SAML, SOC 2 compliance, multiple companies, and dedicated support listed on the pricing page [25]. Fifth, they agreed that Agent Analytics adds a crawler-side view that most citation tools do not offer, tracking how AI bots access and render a site [27].
The agreement is strong but not unanimous on scope. The platforms agreed on what Profound does; they disagreed on how completely it covers the buyer's full end-to-end program, particularly execution.
Where the AI Platforms Disagreed or Were Uncertain
Questions This Section Answers
- Where do AI platforms disagree about Profound's fit for end-to-end AI citation programs?
- Is Profound's pricing and engine coverage consistent across platform reports?
The platforms disagreed on pricing transparency and tier structure. OpenAI and Anthropic both report Starter at $99/month billed yearly and Growth at $399/month billed yearly, with Enterprise custom-priced [29]. Google reports that late-2026 pricing publicly lists only a Trial and custom Enterprise plans, leaving mid-market pricing unclear [31]. Deepseek reported low pricing confidence and no public price sheet [32]. Kimi reported pricing as entirely opaque [33]. Buyers should treat the $399 Growth figure as best-evidenced but not confirmed from the official source.
The platforms disagreed on engine coverage by tier. Anthropic's sources state full coverage requires Enterprise, with Starter limited to ChatGPT only [34]. Google reports up to nine answer engines on Enterprise [31]. Grok reports up to ten engines on Enterprise [35]. OpenAI notes exact availability varies by plan or product configuration [29].
The platforms disagreed on execution completeness. Kimi rated Profound a mixed fit, noting that public materials do not confirm detailed third-party source classification, page-level competitor gap identification with actionability scoring, or automated content brief generation comparable to competitors [36]. OpenAI, Anthropic, Google, and Grok all rated it strong or good, but each noted that Profound does not execute content, PR, outreach, or technical changes on the buyer's behalf [29].
Uncertainty also remains on Agent Analytics granularity. One independent review reports it shows page categories rather than exact URLs, while platform marketing and other reviews describe page-level tracking [40]. The likely explanation is that both categorical and page-level views exist depending on filter and drill-down, but this should be verified in a demo.
Use-Case-Specific Features and Capabilities
Questions This Section Answers
- Does Profound track page-level citations and competitor citations for AI answer engines?
- Can Profound map a category's citation architecture and identify authority gaps?
Profound's capabilities map onto the buyer's seven stated needs as follows.
| Buyer need | Profound capability | Assessment |
|---|---|---|
| Identify domains and pages influencing AI answers | Cited URLs, citation share, source categories, watched-page trends, publishers and authors driving citations | Advantage |
| Measure own and competitor citations | Answer Engine Insights tracks brand and competitor citations, visibility score, visibility rank, citation share, share of voice, sentiment, average position, prompt-level gaps | Advantage |
| Map category citation architecture | Source categories (Owned, Competition, Earned Media, PR Wire, Social, Institution); Profound Index adds topic clusters, co-citation, co-mention, mention position | Advantage |
| Relate citations to recommendations | Connects citation and competitor gaps to page-level content recommendations, head-to-head comparisons, content briefs, outreach targets, Agent workflows | Advantage, with effectiveness dependent on implementation |
| Identify authority gaps | Citation-share analysis and source categorization support authority-gap and earned-media prioritization | Advantage |
| Develop GEO strategy | Prompt and topic monitoring, competitor benchmarking, source categorization, citation-share analysis, content scoring, page health, benchmark comparisons | Advantage as strategy inputs; bespoke consulting deliverables not fully specified |
| Execute improvements over time | Daily prompt collection, historical citation monitoring, watched pages, CSV/JSON exports, integrations, Profound Agents, page-level optimization workflows | Neutral; execution of content, PR, outreach, and technical changes is not established |
Agent Analytics adds a crawler-side diagnostic: it tracks AI crawler visits, indexing, training, agent visits, and human referrals, and can connect to CDNs to bypass JavaScript-based analytics limits [42]. This helps diagnose whether citation gaps stem from crawl barriers or content deficiency.
Pricing, Fees, Contracts, and Ongoing Costs
Questions This Section Answers
- How much does Profound cost per month, and are there setup or cancellation fees?
- What are the contract, renewal, and cancellation terms for Profound Enterprise?
Public pricing lists Starter at $99/month billed yearly and Growth at $399/month billed yearly, with two months free shown for annual billing [44]. Enterprise is custom-priced with tailored packages [44]. Independent sources cite $499/month as a defensible enterprise starting point for teams with five or more brands [46], and one source reports a range of $99 to $5,000+/month by tier [47].
| Plan | Reported price | Reported limits |
|---|---|---|
| Starter | $99/month billed yearly | 50 tracked prompts, ChatGPT tracking, 100 Agent credits/month |
| Growth | $399/month billed yearly | 100 tracked prompts, three answer engines, 400 Agent credits/month |
| Enterprise | Custom quote | Up to nine answer engines, multiple companies, tailored prompt tracking, dedicated Slack support, SSO/SAML, SOC 2 compliance |
Additional fees are unclear. Potential additional cost for expanded Agent credits, higher prompt volume, additional companies, regions, languages, or custom enterprise configuration is not publicly itemized [44]. Consulting, implementation, managed strategy, content production, outreach, and technical execution fees are also not publicly itemized [44].
Contract terms are unclear. The public pricing page identifies annual billing for Starter and Growth but does not state cancellation, refund, renewal, minimum-term, or enterprise termination terms [44]. Independent sources note enterprise contracts move slowly and rarely come with refunds [49]. One source reports no free trial and no self-serve tier, with every conversation starting with a sales call [50], while another reports a limited Trial plan with 10 prompts on ChatGPT only [51]. Buyers should confirm which is current.
Best Suited For
Questions This Section Answers
- Who gets the most value from Profound for AI citation source intelligence and GEO strategy?
- Is Profound best for enterprise teams with dedicated analysts rather than small teams?
Profound is best suited for enterprise teams monitoring citations, competitors, prompts, platforms, regions, and pages over time [52]. It fits companies needing source-intelligence inputs for GEO, content prioritization, earned-media, and authority-gap programs [54]. It also fits organizations that want analytics connected to automated briefs, agents, content workflows, or page-level optimization [52].
Independent sources describe the ideal buyer as an enterprise brand with a dedicated marketing analyst or GEO strategist who can interpret citation data and route fixes to engineering or content teams [57]. Multi-brand portfolios using the enterprise multi-brand view are also a fit [53]. Fortune 500 and mid-market companies already committed to AI visibility as a strategic channel are the core audience, per vendor claims of 10%+ Fortune 500 adoption [59].
Probably Not Best Suited For
Questions This Section Answers
- Who should not choose Profound for AI Citation Partners for Source Intelligence, Strategy, and Execution?
- Is Profound a poor fit for small teams or buyers needing done-for-you GEO execution?
Profound is probably not best suited for small teams needing only basic brand tracking, where the $99/month Starter plan may be sufficient and the enterprise configuration is unnecessary [60]. It is a poor fit for buyers seeking a fully outsourced citation strategy and execution service rather than software-led enablement [60]. It is also a poor fit for use cases requiring transparent, independently audited measurement methodology or guaranteed citation outcomes [60].
Independent sources add that single-brand SMBs or Shopify stores under $5M annual revenue are cost-benefit misaligned, since Profound has no Shopify catalog integration, schema repair, or on-site content updates by design [63]. Teams without dedicated marketing analysts or SEO/content execution processes may find that data alone without an action pathway creates sunk cost [64]. Agencies managing 30+ small client brands at low AUM may find per-brand pricing unfavorable compared with unlimited-client alternatives [65].
When Another Option May Be Better
Questions This Section Answers
- What is a better alternative to Profound for a buyer who needs bundled GEO execution?
- When is a lower-cost or self-serve AI citation tool a better choice than Profound Enterprise?
Another option may be better in several situations. If the buyer needs a fully managed GEO agency that handles strategy and execution end-to-end, a specialist consultancy or agency is a better fit [66]. If the buyer needs bundled citation monitoring plus SEO execution such as schema repair, on-page optimization, and internal linking, platforms like Scalenut, Semrush, or Ahrefs offer both AEO tracking and SEO tooling in one platform [68].
If the buyer operates a multi-client agency with 30+ brands requiring per-client citation tracking at lower cost, Rankability at $199/month covers unlimited clients across nine platforms versus Profound's $399/month per brand [69]. If the buyer needs real user search keywords rather than synthetic proprietary prompts, traditional SEO platforms or SparkToro may be better, since Profound's Conversation Explorer was noted as in development [70]. If the buyer needs done-for-you GEO execution and content production, an agentic marketing platform may be a better single-vendor fit [71].
If the buyer needs to optimize quickly without procurement delays, self-serve platforms offer immediate onboarding versus Profound Enterprise's reported 6-12 week sales cycle [72]. If the buyer prioritizes real-time crawler data at URL-level granularity, other tools may offer finer-grained page-level crawler tracking [73].
Questions to Verify Before Buying
Questions This Section Answers
- What should a buyer confirm with Profound before signing an enterprise contract?
- Which engines, limits, and data-access terms should be verified in the Profound quote?
Before buying, confirm which exact answer engines, models, regions, languages, prompt volumes, and refresh frequencies are included in the quoted Enterprise package [74]. Confirm whether the contract includes Answer Engine Insights, Pages, Agent Analytics, Profound Agents, the Profound Index, and consulting or onboarding services, or whether these are separate products [74].
Confirm how prompts are sourced, sampled, deduplicated, localized, and refreshed, and whether the buyer can export raw responses and citation URLs [74]. Confirm limits for tracked domains, pages, companies, users, historical data, API access, CSV/JSON exports, and integrations [74]. Confirm how citations are attributed when answers contain multiple sources, redirects, syndicated content, or inaccessible URLs [74].
Confirm the Agent credit allotment, what triggers credit consumption, and overage or additional-credit rates [74]. Confirm whether SSO/SAML and SOC 2 are included in the quoted plan and whether current security documentation and data-processing terms are available [74]. Confirm annual commitment, renewal, cancellation, refund, service-level, support, and data-retention terms [74]. Confirm whether Profound provides hands-on execution of content, outreach, PR, or technical changes, and what services are separately billed [74]. Finally, confirm whether a pilot can be run against representative US prompts and compared with manually verified answer-engine responses [74].
Final AI Consensus Verdict
Profound is a strong fit for enterprise AI citation source intelligence, competitive benchmarking, citation-architecture mapping, GEO prioritization, and software-assisted execution. Five of seven platforms named it during ranking discovery, it finished first overall, and four platforms rated the fit strong (openai, anthropic, google, grok), two rated it good (deepseek, perplexity), and one rated it mixed (kimi).
The consensus is that Profound should be treated as an analytics and workflow platform rather than a fully outsourced AI citation consultancy. Its strongest capabilities are page-level citation tracking, competitor citation benchmarking, source categorization, and crawler analytics. Its main limitations are that execution is not bundled, enterprise pricing is quote-only, and independent validation of accuracy, coverage, and customer outcomes is limited in the reviewed sources.
Final purchase suitability depends on validating enterprise scope, methodology, pricing, data access, and whether implementation services are included. Buyers who need end-to-end execution should pair Profound with an agency or content partner rather than expecting a single-vendor solution.
How This Review Was Produced
This review was produced from platform-reported research collected on 2026-09-17 across seven AI platforms: openai (gpt-5.6-luna), anthropic (claude-haiku-4-5-20251001), google (gemini-3.5-flash), grok (x-ai/grok-4.3), perplexity (perplexity/sonar), kimi (moonshotai/kimi-k2.6), and deepseek (deepseek-v4-flash). Each platform evaluated Profound's fit for AI Citation Partners for Source Intelligence, Strategy, and Execution and supplied citations for its claims.
Platform mentions in the ranking stage count only platforms that named Profound during ranking discovery. All seven platforms evaluated fit, but only five named Profound during ranking. The consensus index for this category is available at AI Citation Partners for Source Intelligence, Strategy, and Execution, and the broader category directory is at ai citation authority building.
Methodology Limitations
Several limitations apply. Most available evidence is Profound-owned product documentation and marketing material; independent validation of accuracy, coverage, and customer outcomes is limited in the reviewed sources [80]. Synthetic prompt tracking and real-user-conversation benchmarking are different measurement products, and results may not be directly comparable [80].
Exact enterprise limits, platform availability, regional coverage, prompt volume, data retention, and historical access are not publicly detailed [80]. Software capabilities do not demonstrate that Profound will independently deliver the buyer's full GEO strategy, content production, PR, outreach, or technical deployment [80]. Agent credits and possible overage or expansion fees may create ongoing usage costs [80].
Platform-reported research dates differ from the authoritative run date: deepseek reported 2026-02-14, while the other six platforms reported 2026-09-17. Platform-reported dates are provenance metadata and do not independently prove freshness. The supplied URLs were collected from platform responses and were not independently validated by the writer stage. Citations are platform-reported evidence, not independently verified facts. The deterministic identity audit flagged unresolved identity issues and an unverified matching domain; the website was recovered and verified through web search, but procurement should still confirm the contracting entity and official domain.
Sources
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Additional AI research evidence83 records
- AI research evidence record openai:c2
- AI research evidence record anthropic:citation_2
- AI research evidence record perplexity:c12
- AI research evidence record openai:c6
- AI research evidence record anthropic:citation_21
- AI research evidence record anthropic:citation_8
- AI research evidence record anthropic:citation_15
- AI research evidence record openai:c1
- AI research evidence record anthropic:citation_3
- AI research evidence record perplexity:c1
- AI research evidence record openai:c2
- AI research evidence record anthropic:citation_26
- AI research evidence record openai:c3
- AI research evidence record perplexity:c12
- AI research evidence record anthropic:citation_16
- AI research evidence record google:1.2.3
- AI research evidence record anthropic:citation_18
- AI research evidence record openai:c5
- AI research evidence record grok:web:13
- AI research evidence record openai:c2
- AI research evidence record anthropic:citation_2
- AI research evidence record anthropic:citation_22
- AI research evidence record anthropic:citation_13
- AI research evidence record openai:c6
- AI research evidence record openai:c1
- AI research evidence record anthropic:citation_1
- AI research evidence record anthropic:citation_14
- AI research evidence record google:1.2.3
- AI research evidence record openai:c1
- AI research evidence record anthropic:citation_3
- AI research evidence record google:1.2.1
- AI research evidence record deepseek:c1
- AI research evidence record kimi:profound-site
- AI research evidence record anthropic:citation_5
- AI research evidence record grok:web:5
- AI research evidence record kimi:cited-source-intel
- AI research evidence record kimi:citetrack-source
- AI research evidence record anthropic:citation_8
- AI research evidence record google:1.1.9
- AI research evidence record anthropic:citation_17
- AI research evidence record anthropic:citation_22
- AI research evidence record perplexity:c12
- AI research evidence record google:1.2.3
- AI research evidence record openai:c1
- AI research evidence record anthropic:citation_3
- AI research evidence record anthropic:citation_15
- AI research evidence record anthropic:citation_19
- AI research evidence record deepseek:c4
- AI research evidence record anthropic:citation_12
- AI research evidence record anthropic:citation_7
- AI research evidence record anthropic:citation_10
- AI research evidence record openai:c1
- AI research evidence record anthropic:citation_6
- AI research evidence record openai:c2
- AI research evidence record openai:c6
- AI research evidence record anthropic:citation_18
- AI research evidence record anthropic:citation_24
- AI research evidence record google:1.1.9
- AI research evidence record anthropic:citation_9
- AI research evidence record openai:c1
- AI research evidence record anthropic:citation_8
- AI research evidence record anthropic:citation_28
- AI research evidence record anthropic:citation_15
- AI research evidence record anthropic:citation_24
- AI research evidence record anthropic:citation_12
- AI research evidence record openai:c1
- AI research evidence record deepseek:c4
- AI research evidence record anthropic:citation_11
- AI research evidence record anthropic:citation_12
- AI research evidence record anthropic:citation_25
- AI research evidence record anthropic:citation_8
- AI research evidence record anthropic:citation_7
- AI research evidence record anthropic:citation_17
- AI research evidence record openai:c1
- AI research evidence record perplexity:c1
- AI research evidence record perplexity:c8
- AI research evidence record anthropic:citation_3
- AI research evidence record anthropic:citation_1
- AI research evidence record anthropic:citation_8
- AI research evidence record openai:c1
- AI research evidence record anthropic:citation_28
- AI research evidence record perplexity:c1
- AI research evidence record anthropic:citation_8
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- Profound Review (2026): Is It Worth It for Enterprise AEO?: https://www.vismore.ai/blog/profound-review
Additional AI research evidence83 records
- AI research evidence record openai:c2
- AI research evidence record anthropic:citation_2
- AI research evidence record perplexity:c12
- AI research evidence record openai:c6
- AI research evidence record anthropic:citation_21
- AI research evidence record anthropic:citation_8
- AI research evidence record anthropic:citation_15
- AI research evidence record openai:c1
- AI research evidence record anthropic:citation_3
- AI research evidence record perplexity:c1
- AI research evidence record openai:c2
- AI research evidence record anthropic:citation_26
- AI research evidence record openai:c3
- AI research evidence record perplexity:c12
- AI research evidence record anthropic:citation_16
- AI research evidence record google:1.2.3
- AI research evidence record anthropic:citation_18
- AI research evidence record openai:c5
- AI research evidence record grok:web:13
- AI research evidence record openai:c2
- AI research evidence record anthropic:citation_2
- AI research evidence record anthropic:citation_22
- AI research evidence record anthropic:citation_13
- AI research evidence record openai:c6
- AI research evidence record openai:c1
- AI research evidence record anthropic:citation_1
- AI research evidence record anthropic:citation_14
- AI research evidence record google:1.2.3
- AI research evidence record openai:c1
- AI research evidence record anthropic:citation_3
- AI research evidence record google:1.2.1
- AI research evidence record deepseek:c1
- AI research evidence record kimi:profound-site
- AI research evidence record anthropic:citation_5
- AI research evidence record grok:web:5
- AI research evidence record kimi:cited-source-intel
- AI research evidence record kimi:citetrack-source
- AI research evidence record anthropic:citation_8
- AI research evidence record google:1.1.9
- AI research evidence record anthropic:citation_17
- AI research evidence record anthropic:citation_22
- AI research evidence record perplexity:c12
- AI research evidence record google:1.2.3
- AI research evidence record openai:c1
- AI research evidence record anthropic:citation_3
- AI research evidence record anthropic:citation_15
- AI research evidence record anthropic:citation_19
- AI research evidence record deepseek:c4
- AI research evidence record anthropic:citation_12
- AI research evidence record anthropic:citation_7
- AI research evidence record anthropic:citation_10
- AI research evidence record openai:c1
- AI research evidence record anthropic:citation_6
- AI research evidence record openai:c2
- AI research evidence record openai:c6
- AI research evidence record anthropic:citation_18
- AI research evidence record anthropic:citation_24
- AI research evidence record google:1.1.9
- AI research evidence record anthropic:citation_9
- AI research evidence record openai:c1
- AI research evidence record anthropic:citation_8
- AI research evidence record anthropic:citation_28
- AI research evidence record anthropic:citation_15
- AI research evidence record anthropic:citation_24
- AI research evidence record anthropic:citation_12
- AI research evidence record openai:c1
- AI research evidence record deepseek:c4
- AI research evidence record anthropic:citation_11
- AI research evidence record anthropic:citation_12
- AI research evidence record anthropic:citation_25
- AI research evidence record anthropic:citation_8
- AI research evidence record anthropic:citation_7
- AI research evidence record anthropic:citation_17
- AI research evidence record openai:c1
- AI research evidence record perplexity:c1
- AI research evidence record perplexity:c8
- AI research evidence record anthropic:citation_3
- AI research evidence record anthropic:citation_1
- AI research evidence record anthropic:citation_8
- AI research evidence record openai:c1
- AI research evidence record anthropic:citation_28
- AI research evidence record perplexity:c1
- AI research evidence record anthropic:citation_8
Verify this research
Review the study details behind this page or download the public machine-readable verification record.
- Study date
- September 17, 2026
- Platforms analyzed
- 7
- Source records
- 52
- Ranking mentions
- 5 of 7
- Platform share
- 71%
- Final consensus rank
- #1
Research trail and source mix
Configured platforms
openai, anthropic, deepseek, grok, perplexity, kimi, google
Source mix
31 independent · 21 company-owned
Evidence support
42 direct · 10 partial
Important limitation
Use the run research_date as the study date. Platform-reported dates are provenance metadata and do not independently prove freshness.
Source snapshot SHA-256 acd069fd6840ff4b8cd9c3f2227a44d47f8a540aa9a98c5386bc0fd2a97c3e66