{
  "recordVersion": 1,
  "status": "One completed and independently checked workflow; not an overall comparison verdict",
  "runId": "sales-returns-chatgpt-20261019-03",
  "dateUTC": "2026-10-19",
  "app": "ChatGPT",
  "round": 3,
  "surface": "Ordinary ChatGPT web conversation on the Chat tab (not Work); a fresh chat.",
  "visibleConfiguration": {
    "plan": "Pro (account plan_type pro; exact tier unconfirmed)",
    "modelLabel": "GPT-6",
    "effort": "Pro (5 of 5), the highest available setting",
    "regenerateMenuLabel": "Try again • 6 Pro",
    "backendModelSlug": "gpt-6-pro",
    "connectors": "The app called its first-party Library connector once without an approval prompt (an empty upload-preparation call); nothing was granted or declined and no private data was accessed"
  },
  "configurationScope": "App-reported labels, not independent backend model identification.",
  "operator": "AI browser operator working for Anomaly, using an existing authorized account",
  "reviewer": "Separate scripts written by the article owner recomputed the checked values from the saved input files; the owner also reread the operator record",
  "notBlinded": true,
  "blindingDisclosure": "The operator read the full rubric, the first ~150 lines of the answer key (direct read 21:25:48 UTC, no totals) and the round-2 ChatGPT record, which quotes its results, before sending P1 at 21:29:10 UTC; it read the rest of the key at about 21:43 UTC, after P3 was answered. Only the four frozen prompts and the synthetic workbook were sent; no expected value or hint was sent. Not blinded; the verifying scripts also know the answers.",
  "accountState": "Memory switch OFF as read at the personalization page; the custom-instructions section was present but not opened. A fresh chat does not remove account-level personalization.",
  "independenceDisclosure": "Vendor-authored, not blinded or independent of Anomaly. Unmatched subscriptions and account personalization across apps.",
  "input": {
    "name": "sales-returns-workbook.xlsx",
    "bytes": 2575274,
    "sha256": "5d25f5d9d877c895736cf91361de94742a8f50af8f4d74a1ea2240929e17f3ed",
    "url": "../sales-returns-workbook.xlsx",
    "provenance": "Frozen synthetic five-sheet workbook",
    "upload": "Browser-created File through the app's attachment path (the app renamed the chip to sales-returns-workbook(2).xlsx because earlier copies are in its Library; the in-page hash check of the frozen bytes passed)"
  },
  "reference": {
    "url": "../reference-values.csv",
    "method": "Frozen SQL reference with independent JavaScript and Python/CSV checks"
  },
  "promptsAndInputDownload": "../comparison-workbook-and-checks-v1.zip",
  "prompts": [
    {
      "prompt": "P1",
      "sentUTC": "2026-10-19T21:29:10.324Z",
      "secondsToFinalAnswer": 332
    },
    {
      "prompt": "P2",
      "sentUTC": "2026-10-19T21:36:44.939Z",
      "secondsToFinalAnswer": 159
    },
    {
      "prompt": "P3",
      "sentUTC": "2026-10-19T21:40:53.063Z",
      "secondsToFinalAnswer": 81
    },
    {
      "prompt": "P4",
      "sentUTC": "2026-10-19T21:42:50.031Z",
      "secondsToFinalAnswer": 1604
    }
  ],
  "timingDefinition": "Seconds from the page-clock send click to the app's final-answer message. The shared browser tab may have been hidden, so the page's own completion state can lag the backend. Not an exact generation duration.",
  "access": {
    "allFourPromptsCompletedFirstAttempt": true,
    "clarificationQuestions": 0,
    "recoveryMessages": 0,
    "inConversationQuotaOrAccessBlock": false,
    "toolEventsNotAppEvents": "Another actor navigated the operator's tab after P4 had finished; the run continued in a new tab. P4 ended with the app asking permission to upload files to its file storage; nothing was sent in reply."
  },
  "checks": [
    {
      "id": "N1",
      "check": "All five sheet row counts",
      "result": "PASS",
      "reason": null,
      "observed": "Sales 12,120 (raw) / 12,000 distinct; Returns 600; Products 24; Categories 5; Regions 4",
      "reference": "table_counts: 12120/12000, 600, 24, 5, 4"
    },
    {
      "id": "N2",
      "check": "Key columns and uniqueness",
      "result": "PASS",
      "reason": null,
      "observed": "Sales line_id NOT unique (120 IDs occur twice, exact copies, 12,000 distinct); return_id, product_id, category_id, region_id unique",
      "reference": "integrity_checks / table_counts distinct_keys"
    },
    {
      "id": "N3",
      "check": "Date extents",
      "result": "PASS",
      "reason": null,
      "observed": "Sales.order_date 2026-01-01..2026-06-30; Returns.return_date 2026-01-03..2026-06-30",
      "reference": "date_extents"
    },
    {
      "id": "N4",
      "check": "Three required data-quality observations",
      "result": "PASS",
      "reason": null,
      "observed": "(a) 120 exact repeated Sales rows, 12,120 raw vs 12,000 after (240 rows in pairs, 330 extra units); (b) Seasonal Gifts C5 has no products/sales; (c) no price/revenue/cost fields (\"There are no prices, transaction amounts, refund amounts, or costs\")",
      "reference": "DQ1 120 / DQ2 C5 / DQ3 no price column"
    },
    {
      "id": "N5",
      "check": "Rows before and after deduplication",
      "result": "PASS",
      "reason": null,
      "observed": "12,120 before / 12,000 after (stage table and code output)",
      "reference": "12120 / 12000"
    },
    {
      "id": "N6",
      "check": "Six monthly units totals",
      "result": "PASS",
      "reason": null,
      "observed": "3,456 / 3,761 / 4,872 / 5,643 / 6,815 / 8,559",
      "reference": "units_by_month unique_units"
    },
    {
      "id": "N7",
      "check": "Five category units totals",
      "result": "PASS",
      "reason": null,
      "observed": "C1 9,014; C2 8,535; C3 8,668; C4 6,889; C5 Seasonal Gifts 0 (kept, shown in bold 0)",
      "reference": "units_by_category"
    },
    {
      "id": "N8",
      "check": "Four regional units totals",
      "result": "PASS",
      "reason": null,
      "observed": "R1 11,067; R2 9,090; R3 7,271; R4 5,678",
      "reference": "units_by_region"
    },
    {
      "id": "N9",
      "check": "Grand total and reconciliation",
      "result": "PASS",
      "reason": null,
      "observed": "Grand total 33,106 in all three tables; month, category and region sums each 33,106",
      "reference": "33106 (naive 33,436 not used)"
    },
    {
      "id": "N10",
      "check": "Category return numerators and denominators",
      "result": "PASS",
      "reason": null,
      "observed": "returned/sold: C1 244/9,014; C2 460/8,535; C3 160/8,668; C4 288/6,889; C5 0/0",
      "reference": "return_rate_by_category"
    },
    {
      "id": "N11",
      "check": "Category return rates",
      "result": "PASS",
      "reason": null,
      "observed": "2.71% / 5.39% / 1.85% / 4.18%",
      "reference": "2.71 / 5.39 / 1.85 / 4.18"
    },
    {
      "id": "N12",
      "check": "No-sales category rate",
      "result": "PASS",
      "reason": null,
      "observed": "C5 Seasonal Gifts: \"Undefined\" with the 0 / 0 reason; \"Showing 0.00% would violate the supplied zero-denominator definition\"",
      "reference": "undefined, 0/0"
    },
    {
      "id": "J1",
      "check": "Duplicate-safe joins",
      "result": "PASS",
      "reason": null,
      "observed": "Returned units by category are 244/460/160/288, not the fan-out 248/472/167/293; P1 also computed the raw-join total 1,180 vs 1,152 and named the trap",
      "reference": "not naive_fanout_returned_units"
    },
    {
      "id": "J2",
      "check": "Complete output groups",
      "result": "PASS",
      "reason": null,
      "observed": "5 categories (C5 kept), 4 regions, 6 months present in the tables",
      "reference": "5 / 4 / 6"
    },
    {
      "id": "J3",
      "check": "No invented period or financial values",
      "result": "PASS",
      "reason": null,
      "observed": "No revenue/money amounts or invented values; no month after June in answers, chart, CSV, XLSX or findings text (grep + XLSX date scan); only mentions of revenue are negations (\"Units are not revenue\")",
      "reference": "no revenue, no Jul-Dec values"
    },
    {
      "id": "F1",
      "check": "Chart agrees with checked monthly totals",
      "result": "PASS",
      "reason": null,
      "observed": "Chart PNG (line chart, six points Jan-Jun, y axis \"Units sold\", x axis Jan..Jun, year in subtitle \"January-June 2026\"): printed data labels equal the key exactly; pixel read of the markers against the chart gridlines 3,452 / 3,748 / 4,861 / 5,626 / 6,791 / 8,548 (max error 23.7 units = 1.4 px, 1 px = 17.4 units); XLSX native line chart series Monthly sales!$C$43:$C$48 cached 3456/3761/4872/5643/6815/8559; no month after June",
      "reference": "units_by_month"
    },
    {
      "id": "F2",
      "check": "Exactly three supported findings",
      "result": "PASS",
      "reason": null,
      "observed": "Exactly three findings: June 25.85% of 33,106 (8,559); +5,103 units / +147.66% Jan->Jun and an increase at every step (305, 1,111, 771, 1,172, 1,744); May->June largest unit increase +1,744 (+25.59%). All re-derived from the key; no causal or financial claim",
      "reference": "units_by_month"
    },
    {
      "id": "W1",
      "check": "Reproducible supplied working",
      "result": "PASS",
      "reason": null,
      "observed": "P2 pandas code as shown: run unchanged it stops with FileNotFoundError (its path is the app sandbox path /workspace/scratch/.../sales-returns-workbook(2).xlsx, which exists nowhere else); with ONLY that path line replaced by the frozen workbook path it exits 0 and reproduces months, categories (C5 0), regions, grand total 33,106, 12,120 -> 12,000 rows. P4 script reproduce_monthly_sales.py run UNCHANGED on the frozen workbook (path as the script argument, as its instructions say): exit 0, CSV byte-identical to the delivered CSV, findings text identical after the source filename",
      "reference": "all units_by_*"
    },
    {
      "id": "W2",
      "check": "Working agrees with reported counts and tables",
      "result": "PASS",
      "reason": null,
      "observed": "Shown steps and counts (12,120 -> 12,000, 33,436 - 330 = 33,106, validations) are consistent with the final tables; code output block matches",
      "reference": "grand_total, units_by_*"
    },
    {
      "id": "E1",
      "check": "Delivered files retrieved and reopened",
      "result": "PASS",
      "reason": null,
      "observed": "Six files retrieved (in-page, hash-checked) and reopened: XLSX (openpyxl, LibreOffice), PNG (viewed), CSV (csv module), TXT, PY (executed), ZIP (5 members, each SHA-256 equal to the loose file). Values equal the key and the chat answer",
      "reference": "units_by_month"
    },
    {
      "id": "E2",
      "check": "XLSX summary values",
      "result": "PASS",
      "reason": null,
      "observed": "monthly_sales_summary.xlsx produced, opens in openpyxl and LibreOffice; C7:C12 cached 3456/3761/4872/5643/6815/8559, total 33,106; Sales lines sheet = the 12,000 deduplicated lines (line_id/units pairs equal the CSV-derived dedup set, sum 33,106)",
      "reference": "units_by_month"
    },
    {
      "id": "E3",
      "check": "Claimed workbook editability",
      "result": "PASS",
      "reason": null,
      "observed": "The app claims \"editable chart\", \"visible calculations/formulas\" and a checked source-quantity change. Inspected: 40 formula cells on Monthly sales (SUMIFS/COUNTIFS over Sales lines, EDATE, NA() guard for missing months) + 3 on Sales lines; one native lineChart object. Controlled change Sales lines!E7 1 -> 11 with cached values stripped and LibreOffice recalculation: January 3,456 -> 3,466, total 33,106 -> 33,116, chart source cell C43 3,456 -> 3,466 and the chart cache updated, other months unchanged; the stripped control (unchanged input) equals the key",
      "reference": "-"
    }
  ],
  "scoringNote": "22 separate checks: 22 PASS, 0 FAIL, 0 NOT-ASSESSED. No weighted score or accuracy percentage. Completion, access, timing and cost are separate.",
  "mainDistinction": "Every check passes. Separate defects: the P2 pandas snippet shown in the chat needs its sandbox file path replaced; the app ended P4 by asking to upload files to ChatGPT file storage after its own approval review rejected the upload (nothing was sent in reply); and the fresh page showed the chart as a file chip without an inline image. P4 took about 27 minutes with steady backend activity.",
  "files": [
    {
      "name": "monthly_sales_findings.txt",
      "bytes": 2138,
      "sha256": "c55ed68dbdaea78395d3cd7ddbb86d39c72ca36d8be83bd209513483c13fc565",
      "url": "/blog/best-ai-model-for-data-analysis/r3-chatgpt/monthly_sales_findings.txt",
      "kind": "Unmodified app-delivered file"
    },
    {
      "name": "monthly_sales_results.zip",
      "bytes": 390877,
      "sha256": "1ec81b44e6d4079fb0ce757386e8c6ae68f223656e220caeb618c54f751a5e6b",
      "url": "/blog/best-ai-model-for-data-analysis/r3-chatgpt/monthly_sales_results.zip",
      "kind": "Unmodified app-delivered file"
    },
    {
      "name": "monthly_sales_summary.xlsx",
      "bytes": 419829,
      "sha256": "b2535a66e63d22dac01a406c43626a84e7c731ae01ce0e572f092415eb586f2b",
      "url": "/blog/best-ai-model-for-data-analysis/r3-chatgpt/monthly_sales_summary.xlsx",
      "kind": "Unmodified app-delivered file"
    },
    {
      "name": "monthly_units_sold.csv",
      "bytes": 137,
      "sha256": "11defe4916dab4f90d297bb087d49009276bdc07a8747a2e7e2c50cb4ef4a487",
      "url": "/blog/best-ai-model-for-data-analysis/r3-chatgpt/monthly_units_sold.csv",
      "kind": "Unmodified app-delivered file"
    },
    {
      "name": "monthly_units_sold.png",
      "bytes": 125744,
      "sha256": "4659e7faf2ff80bd6f444f5697c0e980178ece58f794a3cb872458e2e9f91990",
      "url": "/blog/best-ai-model-for-data-analysis/r3-chatgpt/monthly_units_sold.png",
      "kind": "Unmodified app-delivered file"
    },
    {
      "name": "reproduce_monthly_sales.py",
      "bytes": 14609,
      "sha256": "dc4b02344e5efaba9c8636f40f7a7abc2de0f731ef108d48d705807d7dd693e0",
      "url": "/blog/best-ai-model-for-data-analysis/r3-chatgpt/reproduce_monthly_sales.py",
      "kind": "Unmodified app-delivered file"
    }
  ],
  "retrievalMethod": "The delivered files were fetched in-page and hash-matched against copies on the verifying machine; native browser Download buttons were not the retrieval path.",
  "verification": {
    "formulaCells": 43,
    "errorCells": 0,
    "nativeCharts": 1,
    "controlledChange": "One input cell changed on a copy: the total went from 33,106 to 33,116 and the chart updated in LibreOffice",
    "deliveredScriptRerun": "The delivered Python script ran unchanged and reproduced the CSV byte-identically",
    "independentSecondCheck": "writer-r3-chatgpt-independent-verification.json (separate script) confirms the chat figures and the monthly workbook values and grand total"
  },
  "usageAndPrice": "The weekly-limit counter read 0% left both before and after; the page says chat conversations are not counted and no limit message appeared. Pro tier price context is in the article's configuration table.",
  "limitations": [
    "One synthetic fixture, one workflow and one date. Three workflows per app do not estimate population reliability.",
    "No underlying-model, large-file, native add-in, statistical-inference or unattended-refresh conclusion.",
    "Plans, effort settings and account personalization differ across the three apps; this compares app configurations.",
    "Not blinded and vendor-authored."
  ]
}