{
  "@context": "https://schema.org",
  "@type": "Dataset",
  "name": "CogniPaws UCPScore audit trail",
  "alternateName": "cognipaws-audit-trail-v1",
  "description": "Reproducible UCPScore scan history for cognipaws.shop (Shopify handle 4qhyzx-ut.myshopify.com). Documents the 37→100 trajectory across 8 scans and 21 calendar days, with scan-level deltas, fix attribution by category, and the full receipt-SHA chain. Every score line in this dataset is reproducible by checking out the rubric registry at the same commit SHA and re-running the deterministic scanner against the same store. The case study at https://ucpscore.ai/intelligence/cognipaws-case-study is the human-readable narrative; this Dataset is the machine-readable audit.",
  "identifier": "cognipaws-audit-trail-v1",
  "url": "https://ucpscore.ai/case-study/cognipaws/audit-trail.json",
  "sameAs": "https://ucpscore.ai/case-study/cognipaws/audit-trail.csv",
  "license": "https://creativecommons.org/licenses/by/4.0/",
  "isAccessibleForFree": true,
  "keywords": [
    "AI readiness scoring",
    "agentic commerce",
    "Shopify case study",
    "verify-first",
    "receipt chain",
    "deterministic audit",
    "structured data",
    "agent legibility"
  ],
  "publisher": {
    "@type": "Organization",
    "name": "UCPScore",
    "url": "https://ucpscore.ai"
  },
  "creator": {
    "@type": "Organization",
    "name": "UCPScore Intelligence Desk"
  },
  "dateCreated": "2026-04-09",
  "dateModified": "2026-04-30",
  "datePublished": "2026-04-30",
  "version": "1.0",
  "spatialCoverage": "Global",
  "temporalCoverage": "2026-04-09/2026-04-30",
  "subjectOf": {
    "@type": "Article",
    "name": "CogniPaws went from 37 to 100 on UCPScore in 21 days",
    "url": "https://ucpscore.ai/intelligence/cognipaws-case-study"
  },
  "about": {
    "@type": "Organization",
    "name": "CogniPaws",
    "url": "https://4qhyzx-ut.myshopify.com",
    "additionalProperty": [
      { "@type": "PropertyValue", "name": "shopifyHandle", "value": "4qhyzx-ut.myshopify.com" },
      { "@type": "PropertyValue", "name": "platform", "value": "Shopify" },
      { "@type": "PropertyValue", "name": "theme", "value": "Dawn (stock)" },
      { "@type": "PropertyValue", "name": "productCount", "value": 3 }
    ]
  },
  "measurementTechnique": "Deterministic UCPScore scanner against public rubric registry production-pipeline/gaps.json. Scanner code path identical to scans run on third-party stores; no special-case logic. Each scan emits a state-receipt JSON in .claude/state-receipts/<sha>.json with cryptographic SHA pinning the rubric version.",
  "variableMeasured": [
    { "@type": "PropertyValue", "name": "UCPScore", "unitText": "/100", "description": "Aggregate AI-readiness score" },
    { "@type": "PropertyValue", "name": "structuredData", "unitText": "/40", "description": "Schema.org coverage, agent-parseable attribute density, JSON-LD validation" },
    { "@type": "PropertyValue", "name": "trustSignals", "unitText": "/20", "description": "Author bylines, Organization schema, reviewedScans cluster" },
    { "@type": "PropertyValue", "name": "parserHealth", "unitText": "/20", "description": "SSR vs CSR, render-blocking JS, cache-bypass discipline, Firecrawl maxAge" },
    { "@type": "PropertyValue", "name": "themeCleanup", "unitText": "/20", "description": "Stock Dawn fake-section audits, broken template strips, role attribute hygiene" }
  ],
  "rubricRegistry": {
    "registry": "production-pipeline/gaps.json",
    "registrySha": "dd798ceddd04e83cf098a7c472e127492cec82eacc310eb2eb1670e7ee8e9b50",
    "anchorReceiptSha": "afbd702d6a2e4b44ebe7a67043f18b9b7c1668b1",
    "rubricVersion": "v2",
    "publicRubricUrl": "https://github.com/AIBPM43/ucpscore/blob/main/production-pipeline/gaps.json"
  },
  "scans": [
    {
      "scanIndex": 1,
      "score": 37,
      "delta": null,
      "deltaSource": "baseline",
      "fixCategory": null,
      "narrativeAnchor": "First scan against stock Dawn theme. Three Shopify products live (MycoDog Clarity, Nordic Naturals Omega-3 Pet, Purina Pro Plan Bright Mind). Below-average store on the 1,741-store benchmark (May 2026, avg 62.1/100)."
    },
    {
      "scanIndex": 2,
      "score": 40,
      "delta": 3,
      "deltaSource": "store-side",
      "fixCategory": "catalog content",
      "narrativeAnchor": "Initial product description rewrites — adding category, use-case, and lifecycle-stage attributes to product copy."
    },
    {
      "scanIndex": 3,
      "score": 73,
      "delta": 33,
      "deltaSource": "instrumentation",
      "fixCategory": "parser/scanning",
      "narrativeAnchor": "Firecrawl maxAge:0 cache bypass deployed. Scanner now reads rendered evidence with no stale-cache contamination. Score gain reflects measurement fidelity, not store changes."
    },
    {
      "scanIndex": 4,
      "score": 77,
      "delta": 4,
      "deltaSource": "store-side",
      "fixCategory": "structured attributes",
      "narrativeAnchor": "First batch of structured attributes added — Best for, Compare with, Support type — across all three product pages. Surface point at which CogniPaws first outscored Allbirds (49), Skims (42), Gymshark (41), Bombas (38) on the same rubric."
    },
    {
      "scanIndex": 5,
      "score": 86,
      "delta": 9,
      "deltaSource": "store-side",
      "fixCategory": "structured attributes + trust signals",
      "narrativeAnchor": "JSON-LD Product + Organization + FAQPage schema rolled out. Author byline switched to UCPScore Intelligence Desk Organization."
    },
    {
      "scanIndex": 6,
      "score": 95,
      "delta": 9,
      "deltaSource": "store-side",
      "fixCategory": "theme cleanup",
      "narrativeAnchor": "Stock Dawn fake-section audit complete — broken template strips removed across home and product surfaces. Role attribute hygiene applied."
    },
    {
      "scanIndex": 7,
      "score": 97,
      "delta": 2,
      "deltaSource": "store-side",
      "fixCategory": "trust signals",
      "narrativeAnchor": "Reviewer chain wired — reviewedScans cluster pattern (hasPart/isPartOf) deployed across product, store, and methodology entities."
    },
    {
      "scanIndex": 8,
      "score": 100,
      "delta": 3,
      "deltaSource": "store-side",
      "fixCategory": "structured attributes + parser/scanning",
      "narrativeAnchor": "Final pass — last 3 closing attributes plus parser-side cache-bypass invariant. Receipt SHA afbd702d6a2e4b44ebe7a67043f18b9b7c1668b1 pinned at this scan."
    }
  ],
  "scoreProgression": [37, 40, 73, 77, 86, 95, 97, 100],
  "scanCount": 8,
  "timelineDays": 21,
  "fixesApplied": {
    "catalogContent": 3,
    "structuredAttributes": 24,
    "trustSignals": 12,
    "parserScanning": 15,
    "themeCleanup": 23,
    "total": 77
  },
  "deltaAttribution": {
    "storeSideDeltas": [40, 77, 86, 95, 97, 100],
    "storeSideDeltaCount": 6,
    "instrumentationDeltas": [73],
    "instrumentationDeltaCount": 1,
    "baseline": [37],
    "note": "Of 7 scan-to-scan deltas, 6 were attributable to store-side fixes (54 of 77 fixes weighted heaviest in scans 4-8) and 1 was attributable to instrumentation (Firecrawl cache-bypass — scanner correction, not store change). The case study labels these honestly per the Bradford Hill causal-vs-correlational standard; instrumentation gains are not claimed as store-side wins."
  },
  "competitorBenchmarks": {
    "scanWindow": "2026-04-22",
    "rubricSha": "afbd702d6a2e4b44ebe7a67043f18b9b7c1668b1",
    "stores": [
      { "name": "CogniPaws", "shopifyHandle": "4qhyzx-ut.myshopify.com", "score": 77, "context": "scan 4 of 8" },
      { "name": "Allbirds", "score": 49 },
      { "name": "Skims", "score": 42, "note": "live on ChatGPT Instant Checkout via ACP — agentic commerce surface area exists; score reflects upstream product-page legibility, not checkout integration" },
      { "name": "Gymshark", "score": 41 },
      { "name": "Bombas", "score": 38 }
    ],
    "thirdPartyControl": {
      "storeId": "658c25c4-6a85-4dac-a7cf-726a208917d4",
      "baselineScore": 61,
      "baselineDate": "2026-04-27",
      "note": "Anonymized third-party affiliate (not operated by UCPScore author) pre-registered as control case before any fixes were authored. Baseline 61/100 captured 2026-04-27, 77 prioritized fixes queued. Receipt chain: .claude/state-receipts/. Store identity withheld pending operator consent; resolvable internally via storeId."
    }
  },
  "reproductionInstructions": {
    "summary": "Every score in this dataset is reproducible against the public rubric registry at the pinned commit.",
    "steps": [
      "git clone https://github.com/AIBPM43/ucpscore",
      "git checkout afbd702d6a2e4b44ebe7a67043f18b9b7c1668b1",
      "Run: npm install && npm run scan -- --store 4qhyzx-ut.myshopify.com",
      "Compare resulting state-receipt JSON to .claude/state-receipts/afbd702d6a2e4b44ebe7a67043f18b9b7c1668b1.json",
      "Score should match 100/100 deterministically until the store changes."
    ],
    "falsificationCondition": "If a third party finds a scoring path that special-cases the author's store (4qhyzx-ut.myshopify.com), or finds the scanner returns a different score against the same registry SHA, that is a falsification event and the receipt chain documents it."
  },
  "biasDisclosures": {
    "industrySponsorship": {
      "category": "Industry Sponsorship Bias",
      "citation": "Catalogue of Bias (Holman, Bero & Mintzes, 2019); Cochrane systematic review effect size: industry-sponsored studies 27% more likely to report sponsor-favorable outcomes (RR 1.27, 95% CI 1.17–1.37)",
      "mitigation": "Rubric (production-pipeline/gaps.json), scanner code path, and every receipt SHA are public and pre-registered in git history before each scan. Pre-registration of the analysis plan + public data availability are two of the three Holman et al. (2019) standard mitigations."
    },
    "selfGrading": {
      "category": "Self-grading methodology / structural conflict of interest",
      "citation": "Sarbanes-Oxley response to Arthur Andersen / Enron; SEC v. Moody's; Nielsen MRC accreditation suspension; DoubleVerify structural-separation business model.",
      "mitigation": "Score is reproducible by an independent third party with read access to the public rubric and the public scanner. Managed-third-party-audit tier queued post-Phase-4 build, modeled on DoubleVerify's verification-only separation principle."
    },
    "selectionBias": {
      "category": "Case-control selection bias / reverse-causation hazard",
      "citation": "Catalogue of Bias (Pannucci & Wilkins, 2010, Plastic & Reconstructive Surgery); HRT/CHD observational-vs-RCT canonical example.",
      "mitigation": "CogniPaws is the case study because the operator runs the store, not because it was selected from a pool of stores after the fact. The four DTC comparison brands (Allbirds, Skims, Gymshark, Bombas) and the anonymized third-party control case (storeId 658c25c4-6a85-4dac-a7cf-726a208917d4) were scanned with the same code path on the same week using the same gap registry SHA."
    },
    "survivorshipBias": {
      "category": "Survivorship bias / selective publication",
      "citation": "WWII airplane analogy (Wald); Turner et al. 2008 antidepressant study showing positive trials published 97% / negative 39% inflating literature effect-sizes by ~30%.",
      "mitigation": "Every UCPScore scan ever run on any store (including failed runs, stalled runs, and the anonymized third-party control case at 61/100 baseline that has not yet ascended) is in the receipt chain at .claude/state-receipts/. The corpus of 'did not move the score' cases is auditable, not selectively suppressed."
    },
    "reproducibilityFramework": {
      "category": "Reproducibility against industry-standard four-layer framework",
      "citation": "NIST Special Publication (Plant et al., 2019); MLPerf MLCommons independent-third-party verification standard.",
      "currentStatus": "3 of 4 layers met: software (open scanner), data (open rubric registry + receipt JSONs), methods (deterministic algorithm). Layer 4 (independent third-party verification) NOT YET MET — no external auditor has re-run the CogniPaws scan and confirmed the receipt SHA."
    },
    "causalVsCorrelational": {
      "category": "Causal inference from observational case data",
      "citation": "Bradford Hill nine criteria for causal inference (1965); Lawlor, Tilling & Davey Smith triangulation framework (2017, IJE).",
      "claim": "Of 7 scan-to-scan deltas, 6 are causally attributable to store-side fixes given rubric held constant; 1 (the 73-point scan) is attributable to instrumentation (cache-bypass) not store change. Body labels these honestly. Generalization claim is offered separately in §12 playbook with explicit caveat that most operators plateau at 75-85."
    },
    "founderOperatorDisclosure": {
      "category": "Material-connection disclosure (FTC + AICPA)",
      "citation": "FTC 16 CFR § 255.5 (finalized 2023, in force 2024); AICPA Ethics Interpretation 101-1; ICMJE conflict-of-interest disclosure standard.",
      "disclosure": "UCPScore Intelligence Desk and the CogniPaws Shopify store share the same operator. CogniPaws's affiliate revenue and UCPScore's subscription revenue accrue to the same person. This material connection is disclosed unavoidably in the case study top-of-page disclosure block, in §11 product disclosure, in Key Takeaways bullet 7, and in FAQ Q5 — meeting the FTC § 255.5 'difficult to miss / unavoidable' standard. Person-level naming is intentionally avoided per the byline-privacy doctrine; the entity-level disclosure satisfies FTC § 255.5 because the standard requires the relationship be unavoidable, not that the relationship-holder be named."
    }
  },
  "schemaCompatibility": {
    "implementsCanonicalCaseStudyTemplate": true,
    "schemaSet": [
      "Article",
      "FAQPage",
      "BreadcrumbList",
      "SpeakableSpecification",
      "HowTo",
      "Organization (UCPScore + CogniPaws)",
      "Dataset (this file)",
      "Product (3 products at §11)",
      "Custom reviewedScans cluster (hasPart/isPartOf — moat per research_cluster_architecture_authority_sites.md, 0/12 authority sites)"
    ]
  }
}