{
  "schema_version": 1,
  "as_of": "2026-10-23",
  "historical_cutoff": "2026-09-27",
  "scope": "Current verification layer; older primary sources explicitly dated. No canonical research/workbook changes.",
  "status_definitions": {
    "verified": "Narrow statement supported by inspected primary evidence; not the broad economic inference.",
    "partial": "Some factual premises supported; broader scope, causality or primary document remains missing.",
    "unverified": "Exact claim not established in bounded inquiry; absence is not disproof.",
    "contradicted": "Inspected evidence directly conflicts with the exact claim."
  },
  "inquiry_limits": [
    "No original Anthropic draft S-1 or authenticated public filing obtained.",
    "No exact OpenRouter integer export; twelve rounded primary chart weeks now retained, explicitly limited to public telemetry.",
    "No current ranked-spender six-month-delay evidence found in bounded search.",
    "No new paid API or subscription route used.",
    "Aside temporary tab auto-closed at one-shot REPL completion; subsequent source tab explicitly closed."
  ],
  "claims": [
    {
      "id": "CUR-C01",
      "topic": "Anthropic",
      "claim": "Anthropic leaked S-1 is impressive but growth is slowing.",
      "story_points": [],
      "status": "partial",
      "evidence_type": "secondary reporting",
      "metric": "USD recognized-quarter revenue as reported to investors; growth=(16.8/11.5)-1",
      "period": "Q2 and Q3 2026; disclosures October15/20",
      "finding": "Euronews reports Q3 revenue16.8B versus Q2 11.5B:46.1% sequential growth after a more-than-doubling quarter. WSJ reports reviewing a draft prospectus. The original draft was not obtained.",
      "publication_wording": "Reported quarterly revenue still grew rapidly, while its percentage growth slowed. The draft-filing claims remain attributed reporting.",
      "source_ids": [
        "CUR-S01",
        "CUR-S02",
        "CUR-S03"
      ],
      "missing_evidence": [
        "Original draft S-1, version/date and revenue footnotes",
        "Comparable Q1–Q3 financial statements",
        "Definition of adjusted profit and cash-flow adjustments"
      ]
    },
    {
      "id": "CUR-C02",
      "topic": "OpenRouter",
      "claim": "Public OpenRouter token growth slowed in the observed twelve-week window; the latest completed week declined.",
      "story_points": [],
      "status": "verified",
      "evidence_type": "primary visible chart observations and deterministic arithmetic",
      "metric": "Official Top Models chart, nine named models plus Others; prompt+completion tokens; private requests/models/endpoints and zero-data-retention traffic excluded. Derived rates approximate because displays are rounded.",
      "period": "Twelve completed Monday-labelled weeks beginning2026-07-27 through2026-10-12; reconstructed ends throughOctober18; observedOctober23 with page data throughOctober22.",
      "finding": "Twelve primary rounded weekly totals are retained for July27–October18. Equal four-week totals rose294.5T→484T→648T, slowing from+64.3% to+33.9%. Latest week164T fell approximately4.7% from172T; it remains27.1% above four weeks earlier.",
      "publication_wording": "Public OpenRouter token growth decelerated and the latest complete week dipped. This is not evidence of persistent contraction or total-market demand decline.",
      "source_ids": [
        "CUR-S07",
        "CUR-S24"
      ],
      "missing_evidence": [
        "Exact integer daily export and stable-coverage history",
        "Full cache and paid/free splits; realized revenue/compute intensity",
        "Private OpenRouter traffic, direct-provider APIs and first-party apps outside this public series"
      ],
      "original_input_claim": "Overall OpenRouter token usage is slowing.",
      "correction_note": "Accepted primary chart reconstruction supersedes provisional third-party-only status; original broader wording retained in original_input_claim."
    },
    {
      "id": "CUR-C03",
      "topic": "OpenAI",
      "claim": "Two distinct $70B references accompany OpenAI’s reported $50B annualized figure.",
      "story_points": [],
      "status": "partial",
      "evidence_type": "Secondary reporting; original Bloomberg page excerpt retrieved by root",
      "metric": "Annualized revenue, not recognized full-year revenue",
      "period": "End-September 2026 annualized snapshot versus prior presentation; separately a reported year-end 2026 target",
      "finding": "Axios reports $50B versus an earlier $70B presentation on a different partner-sales accounting basis. Separately, Bloomberg’s October 9 original-page excerpt reports roughly $50B annualized revenue at end-September and an expectation to reach or exceed $70B by year-end, citing people familiar with the matter. Neither establishes a realized same-basis forecast miss.",
      "publication_wording": "Axios reported a $50B annualized figure versus an earlier $70B presentation on a different accounting basis. Separately, Bloomberg reported roughly $50B annualized at end-September and an expectation to reach or exceed $70B by year-end, citing people familiar with the matter. The original-page excerpt was retrieved; this verifies the attributed report, not audited financials or a realized same-basis forecast miss as of October 23.",
      "source_ids": [
        "CUR-S04",
        "CUR-S25"
      ],
      "missing_evidence": [
        "Original investor presentation and audited revenue-recognition reconciliation",
        "Underlying company target and accounting comparability across the two reports",
        "Full Bloomberg article not claimed; verified scope is visible original-page excerpt"
      ],
      "original_input_claim": "OpenAI revenue is $50B versus $65B predicted.",
      "correction_note": "User clarified70B on2026-10-23; original65B assertion retained in original_input_claim and verbatim story, not as adopted analysis.",
      "reconciliation_note": "research/current_openai_comparisons.md"
    },
    {
      "id": "CUR-C04",
      "topic": "Meta",
      "claim": "Meta had great earnings; this is bearish for near-term frontier demand.",
      "story_points": [],
      "status": "partial",
      "evidence_type": "primary financials plus analytical inference",
      "metric": "USD consolidated Q3; capex includes finance-lease principal; ex-charge result separate from GAAP",
      "period": "Quarter ended2026-09-30; released2026-10-21",
      "finding": "Q3 revenue64.601B rose26%; GAAP operating income12.988B fell37% but includes9.89B litigation charge. Ex-charge operating income22.88B. Capex34.91B; FCF−2.12B. Strong core monetization does not disclose external frontier-model purchases.",
      "publication_wording": "Meta illustrates monetization inside an established distribution business. The implication for third-party frontier demand is an inference, not a reported result.",
      "source_ids": [
        "CUR-S09"
      ],
      "missing_evidence": [
        "Spend by external lab/model and training/inference",
        "Incremental advertising gross profit causally attributed to specific models",
        "Do not conflate GAAP EPS with charge-adjusted EPS"
      ]
    },
    {
      "id": "CUR-C05",
      "topic": "Tesla",
      "claim": "Tesla had great earnings; this is bearish for near-term frontier demand.",
      "story_points": [],
      "status": "partial",
      "evidence_type": "primary financials plus analytical inference",
      "metric": "USD consolidated quarter; GAAP and adjusted metrics separate",
      "period": "Quarter ended2026-09-30; released2026-10-21",
      "finding": "Q3 revenue28.046B roughly flat YoY; GAAP operating income0.718B down56%; GAAP common net income0.787B down43%; adjusted EPS0.48. Free cash flow1.531B recovered sequentially from−1.092B.",
      "publication_wording": "Tesla’s quarter is mixed across measures. Its operating results do not measure external frontier-language-model demand.",
      "source_ids": [
        "CUR-S10",
        "CUR-S11"
      ],
      "missing_evidence": [
        "Exact meaning of great: consensus beat, sequential recovery, or YoY growth",
        "External model spend; autonomy/training versus general inference split"
      ]
    },
    {
      "id": "CUR-C06",
      "topic": "Financing clocks",
      "claim": "Prepaid, contracted and delayed compute create funding pressure if revenue disappoints.",
      "story_points": [],
      "status": "partial",
      "evidence_type": "primary definition; conditional accounting mechanism",
      "metric": "Stocks of backlog versus period revenue/cash; avoid adding upstream and downstream claims",
      "period": "Current inquiry through2026-10-23; historical packet retains pre-cutoff evidence",
      "finding": "CoreWeave’s disclosed backlog definition is conditional on delivery and service availability. The economic mechanism is valid, but the current inquiry has not reconciled customer minimum payments, delivery triggers, unrestricted cash and financing for a named contract.",
      "publication_wording": "Separate contract signature, prepayment, delivery, billable service and cash collection. Funding stress is a conditional scenario until contract-level obligations are matched.",
      "source_ids": [
        "CUR-S22",
        "CUR-S03"
      ],
      "missing_evidence": [
        "Named contracts, payment schedules, termination rights and delivery remedies",
        "Restricted versus unrestricted funds",
        "Matched supplier/customer financing and revenue cohort"
      ]
    },
    {
      "id": "CUR-C07",
      "topic": "Free and bundled usage",
      "claim": "Dots, Duet, Grok Bot and Google give away proactive usage, contradicting blanket scarcity.",
      "story_points": [],
      "status": "partial",
      "evidence_type": "primary product terms plus inference",
      "metric": "Retail incremental price versus subscription price, quota, marginal cost and capacity",
      "period": "DotsSep29/current helpOct22; DuetOct21; GrokAug26; GoogleMar17 2026",
      "finding": "Dots is bundled with eligible paid plans and deeper-work allowances. Duet is a US Pro/Max waitlist preview with background work counting against shared limits. Grok Bot has separate usage bundled in paid plans. Google extends personal intelligence to free-tier users.",
      "publication_wording": "Some marginal usage is bundled or subsidized. Product terms do not establish unconstrained physical supply; the universal free-agent claim needs these distinctions.",
      "source_ids": [
        "CUR-S13",
        "CUR-S14",
        "CUR-S15",
        "CUR-S16",
        "CUR-S17"
      ],
      "missing_evidence": [
        "Measured proactive usage, compute cost and subsidy by plan",
        "Capacity/time/location, latency and limits",
        "No aggregate utilization conclusion from promotional price alone"
      ]
    },
    {
      "id": "CUR-C08",
      "topic": "Selective routing",
      "claim": "The biggest spenders are shifting to smaller models.",
      "story_points": [],
      "status": "partial",
      "evidence_type": "primary deployment self-report",
      "metric": "Deployment share in a named workflow, not share of total enterprise spending",
      "period": "IntercomMarch26 2026; OpenRouterSeptember2026",
      "finding": "Intercom reports moving approximately100% of English chat/email Fin core answering to its own Apex model from frontier models. OpenRouter shows high open-weight token share, but neither establishes migration by a ranked universe of biggest spenders or model parameter sizes.",
      "publication_wording": "A concrete application vendor reports replacing frontier answering with a specialized model. Broader largest-customer migration remains unmeasured.",
      "source_ids": [
        "CUR-S18",
        "CUR-S05"
      ],
      "missing_evidence": [
        "Ranked spender denominator and before/after bills",
        "Comparable task quality and model size",
        "Retained training/distillation/frontier spending"
      ]
    },
    {
      "id": "CUR-C09",
      "topic": "Waiting option",
      "claim": "Major buyers are waiting six months for cheaper models.",
      "story_points": [],
      "status": "unverified",
      "evidence_type": "unsupported generalization",
      "metric": "Buyer count, budget deferred, delay length and counterfactual benefit unknown",
      "period": "As of2026-10-23",
      "finding": "A bounded search did not locate a current named major-buyer disclosure establishing this exact behavior or its scale. This is not proof that such behavior does not occur.",
      "publication_wording": "Treat waiting as an explicit scenario assumption, not an observed industry rate.",
      "source_ids": [],
      "missing_evidence": [
        "Named buyer/decision-maker statement",
        "Original publication and date",
        "Workload, deferred dollars and actual adoption date"
      ]
    },
    {
      "id": "CUR-C10",
      "topic": "Personal assistants",
      "claim": "Altman says Dot saves him one hour a day.",
      "story_points": [],
      "status": "verified",
      "evidence_type": "primary original video captions",
      "metric": "Self-estimated time saved per person per day; no measured counterfactual",
      "period": "Interview published2026-10-21",
      "finding": "Original YouTube captions place his estimate at13:23–13:29. Publication metadata is2026-10-21T08:30:24−07:00. This is a personal estimate, not measured cash savings or a universal productivity ceiling.",
      "publication_wording": "At13:23, Altman estimates Dot saves him an hour daily on unwanted work.",
      "source_ids": [
        "CUR-S12"
      ],
      "missing_evidence": [
        "Independent time-use measurement",
        "Configuration and ultrafast status",
        "Whether saved time becomes output, leisure or paid payroll reduction"
      ],
      "supporting_notes": [
        "Supplied workbook S22 separately attributes a September 30 Every interview without an original URL (V2 slide 10). That source identity remains unresolved and is not established by the verified October 21 Matthew Berman video. The verified one-hour quote and its timestamp remain unchanged."
      ]
    },
    {
      "id": "CUR-C11",
      "topic": "Coding review",
      "claim": "AI coding creates review, rework and bug costs.",
      "story_points": [],
      "status": "partial",
      "evidence_type": "primary research with scope limits",
      "metric": "Review workload and original code contribution; not company profit or all October2026 tools",
      "period": "Studyv3January28 2026; METR updateFebruary24 2026",
      "finding": "An OSS/Copilot study reports more review/rework concentrated on core developers. METR’s February2026 update warns its later productivity estimates are unreliable because of selection and measurement effects. No current all-coding net-loss estimate follows.",
      "publication_wording": "Review and rework are real cost categories; measure net delivery time and escaped defects alongside generation speed.",
      "source_ids": [
        "CUR-S19",
        "CUR-S20"
      ],
      "missing_evidence": [
        "Representative current-model controlled workload",
        "Review time, incident costs, maintenance and accepted output",
        "Cash realization versus saved capacity"
      ]
    },
    {
      "id": "CUR-C12",
      "topic": "Physical experimentation",
      "claim": "Biotech has brains without legs: intelligence cannot instantly remove lab and trial bottlenecks.",
      "story_points": [],
      "status": "partial",
      "evidence_type": "primary process evidence; economic analogy",
      "metric": "Workflow stages and indicative study duration, not AI-specific investment return",
      "period": "FDA guidance accessed2026-10-23",
      "finding": "FDA describes preclinical evidence, human trials and review as distinct steps; Phase2 commonly lasts months to2years and Phase3 one to4years. This supports a physical-validation lag, not a fixed cap on biotech AI demand.",
      "publication_wording": "More candidate designs still require experiments and clinical validation before becoming approved treatments.",
      "source_ids": [
        "CUR-S21"
      ],
      "missing_evidence": [
        "Named program bottleneck and compute spend",
        "Laboratory throughput, trial endpoints and approval pathway",
        "Evidence that faster design does or does not expand experimental demand"
      ]
    },
    {
      "id": "CUR-C13",
      "topic": "Token economics",
      "claim": "Rising token totals can overstate growth in expensive compute and revenue.",
      "story_points": [],
      "status": "verified",
      "evidence_type": "primary platform telemetry",
      "metric": "Agent/human API-key token ratio; cached-prompt share of all agent tokens. Cache rate itself=cached prompt/total prompt.",
      "period": "September2026; newsletterOctober8",
      "finding": "OpenRouter reports agentic tokens7x human tokens in the last week of September and cached prompts just under90% of all agent tokens. Its classifier and reseller exclusion limit scope; cached tokens, novel inputs and outputs have different economics.",
      "publication_wording": "Track token type and realized price: a cached token is not the same economic unit as a newly generated output token.",
      "source_ids": [
        "CUR-S06"
      ],
      "missing_evidence": [
        "Realized provider price and compute intensity by token type",
        "Direct-API and first-party-app coverage"
      ]
    },
    {
      "id": "CUR-C14",
      "topic": "Macroeconomic scale",
      "claim": "A10–20% GDP expansion implies trillions of dollars of additional output.",
      "story_points": [
        10
      ],
      "status": "verified",
      "evidence_type": "primary government table plus arithmetic",
      "metric": "Nominal annual2025 GDP, revised vintage availableOctober7 2026. Not Q2 annualized GDP, real growth, cumulative revenue or gross output.",
      "period": "Calendar2025; postSeptember27 source vintage",
      "finding": "Official table gives2025 US nominal GDP of30,861.3B USD.10–20% of that baseline is3,086.13–6,172.26B. These are arithmetic scale equivalents, not forecasts or frontier-model revenue.",
      "publication_wording": "Using2025 US nominal GDP ofabout30.9T as a scale reference,10–20% isabout3.1–6.2T of additional value added.",
      "source_ids": [
        "CUR-S23"
      ],
      "missing_evidence": [
        "Causal AI contribution and horizon",
        "Pass-through from value added to enterprise profit and model-provider receipts",
        "Price/inflation treatment for an intertemporal growth projection"
      ]
    }
  ],
  "sources": [
    {
      "id": "CUR-S01",
      "title": "Anthropic raises $65B Series H",
      "publisher": "Anthropic",
      "source_type": "primary",
      "published_at": "2026-05-28",
      "accessed_at": "2026-10-23T14:10:14.149571+00:00",
      "locator": "Announcement opening paragraphs",
      "url": "https://www.anthropic.com/news/series-h"
    },
    {
      "id": "CUR-S02",
      "title": "Anthropic revenue jumps 46% to $16.8bn",
      "publisher": "Euronews",
      "source_type": "secondary",
      "published_at": "2026-10-15T10:57:00+02:00",
      "accessed_at": "2026-10-23T14:10:14.149571+00:00",
      "locator": "Article paragraphs 1–6",
      "url": "https://www.euronews.com/2026/10/15/anthropic-revenue-jumps-46-to-168bn-as-ai-firm-eyes-record-2-trillion-ipo-valuation"
    },
    {
      "id": "CUR-S03",
      "title": "Anthropic S-1 Shows Red-Hot Growth, Risks and Massive Computing Costs",
      "publisher": "Wall Street Journal",
      "source_type": "secondary",
      "published_at": "2026-10-20",
      "accessed_at": "2026-10-23T14:10:14.149571+00:00",
      "locator": "Headline, subheading and accessible opening",
      "url": "https://www.wsj.com/tech/ai/anthropic-revenue-growth-ipo-accaf0f1"
    },
    {
      "id": "CUR-S04",
      "title": "OpenAI annualized revenue $20 billion less than previously reported",
      "publisher": "Axios",
      "source_type": "secondary",
      "published_at": "2026-10-08T19:50:13Z",
      "accessed_at": "2026-10-23T14:10:14.149571+00:00",
      "locator": "Opening and partner-sales accounting explanation",
      "url": "https://www.axios.com/2026/10/08/openai-50-billion-arr-anthropic-revenue-accounting"
    },
    {
      "id": "CUR-S05",
      "title": "The Token State of Play",
      "publisher": "OpenRouter",
      "source_type": "primary",
      "published_at": "2026-09-22",
      "accessed_at": "2026-10-23T14:10:14.149571+00:00",
      "locator": "Whole-pie growth and open/closed model sections",
      "url": "https://openrouter.ai/data/newsletter/the-token-state-of-play"
    },
    {
      "id": "CUR-S06",
      "title": "Cache is Crucial",
      "publisher": "OpenRouter",
      "source_type": "primary",
      "published_at": "2026-10-08",
      "accessed_at": "2026-10-23T14:10:14.149571+00:00",
      "locator": "Agents now run the show; Cache rules everything; methodology footer",
      "url": "https://openrouter.ai/data/newsletter/cache-is-crucial"
    },
    {
      "id": "CUR-S07",
      "title": "AI Model Rankings",
      "publisher": "OpenRouter",
      "source_type": "primary",
      "published_at": null,
      "accessed_at": "2026-10-23T14:10:14.149571+00:00",
      "locator": "Top Models; leaderboard; How these rankings are measured",
      "url": "https://openrouter.ai/rankings"
    },
    {
      "id": "CUR-S08",
      "title": "AI Token Usage Tracker",
      "publisher": "TokenDealHub",
      "source_type": "secondary",
      "published_at": null,
      "accessed_at": "2026-10-23T14:10:14.149571+00:00",
      "locator": "Latest day, last full week, smoothing and methodology",
      "url": "https://www.tokendealhub.com/en/token-usage"
    },
    {
      "id": "CUR-S09",
      "title": "Meta Reports Third Quarter 2026 Results",
      "publisher": "Meta via PRNewswire",
      "source_type": "primary",
      "published_at": "2026-10-21T16:01:00-04:00",
      "accessed_at": "2026-10-23T14:10:14.149571+00:00",
      "locator": "Financial highlights, litigation adjustment, CFO outlook",
      "url": "https://www.prnewswire.com/news-releases/meta-reports-third-quarter-2026-results-302915964.html"
    },
    {
      "id": "CUR-S10",
      "title": "Tesla Q3 2026 Update",
      "publisher": "Tesla",
      "source_type": "primary",
      "published_at": "2026-10-21",
      "accessed_at": "2026-10-23T14:10:14.149571+00:00",
      "locator": "PDF page4 financial summary; page3 narrative",
      "url": "https://assets-ir.tesla.com/tesla-contents/IR/TSLA-Q3-2026-Update.pdf"
    },
    {
      "id": "CUR-S11",
      "title": "Tesla Q3 2026 Form 10-Q",
      "publisher": "Tesla / SEC",
      "source_type": "primary",
      "published_at": "2026-10-22",
      "accessed_at": "2026-10-23T14:10:14.149571+00:00",
      "locator": "Statements of operations; MD&A",
      "url": "https://www.sec.gov/Archives/edgar/data/1318605/000162828026066775/tsla-20260930.htm"
    },
    {
      "id": "CUR-S12",
      "title": "Sam Altman: RSI, AI Consciousness, OpenAI’s New Hardware, Compute, and more!",
      "publisher": "Matthew Berman",
      "source_type": "primary",
      "published_at": "2026-10-21T08:30:24-07:00",
      "accessed_at": "2026-10-23T14:10:14.149571+00:00",
      "locator": "YouTube captions13:23–13:29; personal-assistant chapter11:47",
      "url": "https://www.youtube.com/watch?v=3gXLmy7DK_4&t=803s"
    },
    {
      "id": "CUR-S13",
      "title": "Introducing dots",
      "publisher": "OpenAI",
      "source_type": "primary",
      "published_at": "2026-09-29",
      "accessed_at": "2026-10-23T14:10:14.149571+00:00",
      "locator": "Get started with dots and Dots can work on their own",
      "url": "https://openai.com/index/introducing-dots/"
    },
    {
      "id": "CUR-S14",
      "title": "Getting started with your dot",
      "publisher": "OpenAI",
      "source_type": "primary",
      "published_at": "2026-10-22",
      "accessed_at": "2026-10-23T14:10:14.149571+00:00",
      "locator": "Which plans include dots?",
      "url": "https://help.openai.com/en/articles/20001530-getting-started-with-your-dot"
    },
    {
      "id": "CUR-S15",
      "title": "Introducing Claude Duet",
      "publisher": "Anthropic",
      "source_type": "primary",
      "published_at": "2026-10-21",
      "accessed_at": "2026-10-23T14:10:14.149571+00:00",
      "locator": "Opening; How Claude Duet works; Join research preview",
      "url": "https://claude.com/resources/articles/claude-duet"
    },
    {
      "id": "CUR-S16",
      "title": "Grok Bot is now included with more plans",
      "publisher": "SpaceXAI",
      "source_type": "primary",
      "published_at": "2026-08-26",
      "accessed_at": "2026-10-23T14:10:14.149571+00:00",
      "locator": "Plan list and separate usage paragraph",
      "url": "https://x.ai/news/grok-bot-more-plans"
    },
    {
      "id": "CUR-S17",
      "title": "Bringing the power of Personal Intelligence to more people",
      "publisher": "Google",
      "source_type": "primary",
      "published_at": "2026-03-17",
      "accessed_at": "2026-10-23T14:10:14.149571+00:00",
      "locator": "Article body availability paragraph",
      "url": "https://blog.google/products-and-platforms/products/search/personal-intelligence-expansion/"
    },
    {
      "id": "CUR-S18",
      "title": "Announcing Fin Apex: The age of vertical models is here",
      "publisher": "Intercom / Eoghan McCabe",
      "source_type": "primary",
      "published_at": "2026-03-26",
      "accessed_at": "2026-10-23T14:10:14.149571+00:00",
      "locator": "The news, core answering model paragraph",
      "url": "https://www.intercom.com/blog/announcing-fin-apex-the-age-of-vertical-models-is-here"
    },
    {
      "id": "CUR-S19",
      "title": "AI-Assisted Programming Decreases the Productivity of Experienced Developers by Increasing the Technical Debt and Maintenance Burden",
      "publisher": "Xu et al.",
      "source_type": "primary",
      "published_at": "2026-01-28T12:11:30Z",
      "accessed_at": "2026-10-23T14:10:14.149571+00:00",
      "locator": "Abstract; version3",
      "url": "https://arxiv.org/abs/2510.10165v3"
    },
    {
      "id": "CUR-S20",
      "title": "We are Changing our Developer Productivity Experiment Design",
      "publisher": "METR",
      "source_type": "primary",
      "published_at": "2026-02-24",
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