Research/Terra/ 476053
Task evidence / county-choropleth

Map the distribution of tuberculosis cases across Massachusetts counties.

PassComputational taskUnpublished draft
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The question

476053
Map the distribution of tuberculosis cases across Massachusetts counties.
Exact submitted task and declared adaptations
Map the distribution of tuberculosis cases across Massachusetts counties. 

Task conventions: Use Census TIGER/Line 2024 original county polygons with STATEFP='25', and the frozen Massachusetts 2023 TB table. Map the published TB case RATE per 100,000 people, following the first released reference method; retain Number of Cases as supporting information. Join NAME to County exactly after selecting the state. Footnotes and totals are not counties. Keep all matching original county features, source geometry and benchmark_row_id. Genuine zero cases and zero rates remain zero; unknown measurements remain unknown. Do not substitute current rates or infer individual patient locations. Use five quantile classes (collapse ties), upper class on equal breaks, and a distinct neutral No data category with numeric bounds and units in the legend. This is a county-level public aggregate, not a patient map or medical risk recommendation.



Publish an inspectable county data artifact and add its quantitative map. End with one fenced JSON object containing count (known counties), unknown_count (unknown counties), coverage_note, selection: {collectionId,itemId,assetKey}, value_field, class_field and map_layer_id. Explain the year, rate versus count distinction, and county-level limitations.

Delivery format: provide the answer object with all fields specified above as final_response on assess_result, alongside the inspected final artifact_refs. This replaces the JSON-code-block formatting requirement above. Blue attaches your explicit selection to the accepted final answer. Finish with a concise ordinary-language answer agreeing with that selected result; do not duplicate the JSON in chat.

Supplied immutable inputs:
[
  {
    "name": "US county boundaries",
    "edition": "Census TIGER/Line 2024",
    "units": {},
    "collectionId": "blue-generated--[resource id withheld]",
    "itemId": "[resource id withheld]",
    "assetKey": "data"
  },
  {
    "name": "Massachusetts county tuberculosis cases and published rates, 2023",
    "edition": "Massachusetts DPH 2023 summary, frozen GeoBenchX transcription",
    "units": {
      "Number of Cases": "cases",
      "TB Case Rate[1] 2023(cases per 100,000)": "cases per 100,000 people"
    },
    "collectionId": "blue-generated--[resource id withheld]",
    "itemId": "[resource id withheld]",
    "assetKey": "data"
  }
]

Outcome & verification

Independent artifact and delivery checks passed.

Duration
18m 37s
Recorded Blue tool calls
48
Total tokens
1,821,906
Model cost
Not recorded
Application revision
d50497ea9084f29c91b05406688f87035df98d8a
Release
terra-geobenchx-v1

Recorded final answer

Done. The inspectable county artifact and quantitative map are on your map. It shades counties by the published 2023 TB case rate per 100,000 people and keeps Number of Cases as supporting county data. All 14 Massachusetts counties are included, and none have unknown published rates. Important limit: this is a county-level 2023 public aggregate, so it does not show patient locations, current conditions, or medical risk. Because several counties share the same published rate, the requested five quantiles collapse to four displayed class codes. Next step: click any county to review its 2023 rate, case count, and preserved benchmark row ID. Sources: U.S. Census Bureau, TIGER/Line 2024 county boundaries; Massachusetts Department of Public Health, 2023 Tuberculosis Summary Data, frozen GeoBenchX transcription, retrieved 2026-10-07. ### Limitations - Published rates and counts describe 2023 summary values only; they do not represent current conditions. - Five requested quantiles collapse to four numeric class codes here because several counties share the same published rate. - This is a county-level public aggregate from the frozen 2023 summary, not individual patient locations or a medical risk recommendation. - The rates and counts describe published 2023 conditions only; they do not represent current conditions. - County boundaries do not show where cases occurred within each county. - These are published 2023 county aggregates, not current conditions. - The exact join confirms county matches only; it does not locate cases within counties. - No county rate is unknown in the supplied 2023 county table, so the No data category is available but unused.

Independent checks

These checks are separate from the agent's own assessment. A successful job or an assertion of success is not enough to pass.

Expected count
14
Reported count
14
Computation verified
Yes
Answer fulfilled
Yes
Full grading and rubric record
{
  "expectedCount": 14,
  "actualCount": 14,
  "expectedMetrics": null,
  "actualMetrics": null,
  "computationCorrect": true,
  "answerFulfilled": true,
  "adjudication": null,
  "qualification": null,
  "reasons": []
}

Recorded investigation findings

The agent's reported hypotheses and assessments, retained as evidence of its process—not independent proof that the answer is correct. Failed calls retain their requested verdict, not an accepted assessment.

run_trial · completed

Do the supplied county and TB source rows expose the exact fields needed for Massachusetts county selection, exact NAME-to-County joining, and exclusion of non-county rows?

assess_trial · completed · assessment: sufficient

The supplied county source exposes STATEFP, NAME, and benchmark_row_id. Filtering STATEFP='25' returns 14 Massachusetts counties with distinct county names and preserved benchmark_row_id values. The supplied TB table exposes County, Number of Cases, and TB Case Rate[1] 2023(cases per 100,000). Inspecting all 15 rows shows 14 county rows plus one footnote row with null cases and null rate; no separate total row appears in the supplied table.

run_trial · completed

Does the full Massachusetts method preserve the 14 original county polygons, join the published 2023 TB values by exact NAME-to-County, exclude the footnote row, and produce a quantitative rate class field with quantile classes and valid zeros?

assess_trial · completed · assessment: sufficient

The full Massachusetts method produced 14 county features after filtering STATEFP='25', preserving the original county geometry and benchmark_row_id values. The exact left join by NAME to County matched all 14 counties with 0 unmatched input features and copied Number of Cases plus TB Case Rate[1] 2023(cases per 100,000) for every county. The footnote row in the table did not join because it is not a county name. The classified county output kept the published rate field, retained genuine zero rates and zero case counts as valid zeros, and added rate_class. Because repeated quantiles collapsed, the final class field contains 4 classes rather than 5 numeric class codes, which is the expected tie-collapse behavior for five requested quantiles. No county rate is unknown in the joined output, so no county falls into a No data class.

assess_result · failed · requested assessment: sufficient

The published final artifact contains 14 Massachusetts county polygons from Census TIGER/Line 2024 with preserved benchmark_row_id, the frozen Massachusetts 2023 Number of Cases field, the published 2023 TB case rate per 100,000 people, and a rate_class field. The final map layer is on the current map as layer [resource id withheld]. All 14 Massachusetts counties have known published rates. Because several counties share the same published rate, the requested five quantiles collapse to four numeric class codes in the final classified output.

assess_result · completed · assessment: sufficient

The published final artifact contains 14 Massachusetts county polygons from Census TIGER/Line 2024 with preserved benchmark_row_id, the frozen Massachusetts 2023 Number of Cases field, the published 2023 TB case rate per 100,000 people, and a rate_class field. The final map layer is on the current map as layer [resource id withheld]. All 14 Massachusetts counties have known published rates. Because several counties share the same published rate, the requested five quantiles collapse to four numeric class codes in the final classified output.

Recorded workflow

  1. 01

    TB rate classes

    Recorded vector-classify · succeeded

  2. 02

    Supplied county polygons

    Recorded source · succeeded

  3. 03

    Massachusetts county tuberculosis rates, 2023

    Recorded output · succeeded

  4. 04

    County TB join

    Recorded table-attribute-join · succeeded

  5. 05

    Massachusetts counties

    Recorded vector-filter · succeeded

  6. 06

    Frozen Massachusetts TB table

    Recorded source · succeeded

  7. 07

    TB rate classes

    Recorded vector-classify · succeeded

  8. 08

    Supplied county polygons

    Recorded source · succeeded

  9. 09

    County TB join

    Recorded table-attribute-join · succeeded

  10. 10

    Massachusetts counties

    Recorded vector-filter · succeeded

  11. 11

    Frozen Massachusetts TB table

    Recorded source · succeeded

  12. 12

    County TB join

    Recorded output · succeeded

  13. 13

    TB rate classes

    Recorded output · succeeded

  14. 14

    Supplied county polygons

    Recorded source · succeeded

  15. 15

    Supplied Massachusetts TB table

    Recorded source · succeeded

  16. 16

    Supplied county polygons

    Recorded output · succeeded

  17. 17

    Supplied Massachusetts TB table

    Recorded output · succeeded

Activity

Recorded actions

Recorded observable actions only, not private reasoning. Raw payloads, geometry, private links and credentials are omitted; full evidence is retained privately. Activity/workflow lists bounded at 500 entries.

  1. Progress update

    I’ll check the saved analysis context and the exact collection schemas first, then I’ll test the county join and classing method before I publish the map.

  2. Progress update

    I’ve got the Blue geospatial tools. Next I’m inspecting the two supplied datasets so I can use their exact fields and then pick the right join and classing processors.

  3. get_collection

    Recorded tool call · completed

  4. get_analysis

    Recorded tool call · completed

  5. list_processors

    Recorded tool call · completed

  6. get_collection

    Recorded tool call · completed

  7. Progress update

    I found the likely processors: filter the county polygons, join the frozen TB table by name, then classify the published rate with quantiles. I’m now reading the exact field samples and processor schemas so I can test the real method rather than guess it.

  8. get_tool_help

    Recorded tool call · completed

  9. describe_processors

    Recorded tool call · completed

  10. get_tool_help

    Recorded tool call · completed

  11. get_tool_help

    Recorded tool call · completed

  12. get_tool_help

    Recorded tool call · completed

  13. Progress update

    I have the processor contracts. The remaining uncertainty is the exact field names and whether the frozen TB table has any totals or footnotes that must stay out of the join, so I’m testing that directly now.

  14. get_tool_help

    Recorded tool call · completed

  15. get_tool_help

    Recorded tool call · completed

  16. Progress update

    I still need the live row samples. I’m trying a bounded collection inspection first so I can avoid a malformed join request and confirm the exact county and rate columns.

  17. get_collection

    Recorded tool call · completed

  18. get_collection

    Recorded tool call · completed

  19. Progress update

    I’m recording the analytical goal now so the join test and final verification use the same required checks all the way through.

  20. update_analysis_brief

    Recorded tool call · completed

  21. Progress update

    I expect the county file to expose the TIGER county key fields like STATEFP and NAME, and the TB table to expose County, Number of Cases, the published 2023 rate field, plus at least one non-county row to exclude. That will confirm the exact join keys and exclusion rule before I build the final map workflow.

  22. run_trial

    Recorded tool call · completed

  23. Progress update

    The source check succeeded. I found the needed fields on both inputs, including the long footnote text in the TB table’s County column. I’m pulling the actual Massachusetts county rows now so I can verify the exact join matches and the final county count before I publish anything.

  24. inspect_artifact

    Recorded tool call · completed

  25. get_trial_report

    Recorded tool call · completed

  26. inspect_artifact

    Recorded tool call · completed

  27. Progress update

    The source check answered the field question. I’m now testing the actual full method on the real Massachusetts counties: state filter, exact NAME-to-County join, and quantile classing of the published 2023 rate.

  28. inspect_artifact

    Recorded tool call · completed

  29. inspect_artifact

    Recorded tool call · completed

  30. get_tool_help

    Recorded tool call · completed

  31. get_tool_help

    Recorded tool call · completed

  32. Progress update

    The inputs are now confirmed: 14 Massachusetts county polygons from TIGER/Line 2024, and 15 TB-table rows made up of 14 counties plus one footnote row. I’m recording that check, then I’ll test the joined county map itself.

  33. assess_trial

    Recorded tool call · completed

  34. Progress update

    I expect this full-state test to return 14 Massachusetts county features with the original geometry and benchmark_row_id, a complete exact join from the 14 county rows in the TB table, and a rate class field built from quantiles where zeros stay valid zeros. If the join or classes fail here, I can correct the method before I save the final workflow.

  35. run_trial

    Recorded tool call · completed

  36. Progress update

    The statewide method test worked: 14 county polygons in, 14 counties matched, no county join gaps, and the published rate field classified successfully. I’m checking the exact class values and preview now, then I’ll save the final workflow and publish the county map layer.

  37. inspect_artifact

    Recorded tool call · completed

  38. inspect_artifact

    Recorded tool call · completed

  39. get_trial_report

    Recorded tool call · completed

  40. Progress update

    I’m verifying the finished county table itself before I publish it: exact joined rows, the rate class field, and the map preview/legend behavior. Then I’ll save the tested workflow and add the map layer.

  41. inspect_artifact

    Recorded tool call · completed

  42. inspect_artifact

    Recorded tool call · completed

  43. get_tool_help

    Recorded tool call · completed

  44. get_tool_help

    Recorded tool call · completed

  45. Progress update

    The tested method is ready. It keeps the original county polygons, matches all 14 counties exactly, excludes the footnote row naturally because it is not a county name, and collapses tied quantiles to 4 rate classes because several counties have the same published rate. I’m recording that, then I’ll save and run the production workflow.

  46. assess_trial

    Recorded tool call · completed

  47. Progress update

    I’ve finished method testing. I’m pulling the remaining workflow schemas now so I can save the final draft cleanly, then I’ll run it and bind the map layer from the verified output.

  48. get_tool_help

    Recorded tool call · completed

  49. get_tool_help

    Recorded tool call · completed

  50. get_tool_help

    Recorded tool call · completed

  51. get_tool_help

    Recorded tool call · completed

  52. get_tool_help

    Recorded tool call · completed

  53. Progress update

    I have the proposal pieces. I’m checking one last schema for the workflow requirement explanations so the saved draft carries the current evidence and not stale setup notes.

  54. update_analysis_brief

    Recorded tool call · completed

  55. Progress update

    I’m saving the tested production draft now. It uses the exact method that already worked statewide, so the remaining step is execution and map binding, not more method repair.

  56. propose_workflow

    Recorded tool call · completed

  57. Progress update

    The draft is ready and matches the tested statewide method. I’m running that exact workflow now, then I’ll inspect the produced county artifact and bind its map layer.

  58. execute_workflow

    Recorded tool call · completed

  59. Progress update

    The workflow run finished in the background. I’m inspecting the produced output now so I can bind the exact final county artifact, add its map layer, and record the final answer against the verified result.

  60. list_map_layers

    Recorded tool call · completed

  61. inspect_workflow_results

    Recorded tool call · completed

  62. Progress update

    I have the final county artifact and its map layer on the map. I’m doing one bounded final inspection of the exact published output now so the recorded result points to the final artifact, not just the trial copy.

  63. inspect_artifact

    Recorded tool call · completed

  64. get_tool_help

    Recorded tool call · completed

  65. Progress update

    The final output inspection is ready. I’m reading that exact final preview now so the accepted result points to the published county artifact and current map layer, not the earlier trial copy.

  66. inspect_artifact

    Recorded tool call · completed

  67. get_tool_help

    Recorded tool call · completed

  68. Progress update

    I’m recording the final result now with the published county artifact selection and the live map layer ID from the current map.

  69. assess_result

    Recorded tool call · failed

  70. Progress update

    I’m correcting the final assessment to use the exact required condition list from the saved result, then I’ll finish the ordinary-language answer.

  71. assess_result

    Recorded tool call · completed

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