Research/Terra/ 908870
Task evidence / country-choropleth

Visualize total population distribution by country

PassComputational taskUnpublished draft
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The question

908870
Visualize total population distribution by country.
Exact submitted task and declared adaptations
Visualize total population distribution by country.

Task conventions: Use the frozen country polygons and World Bank SP.POP.TOTL 2023 column, in people. These are country-level indicators, not a subnational surface or a new regional aggregation. Join the supplied ISO_A3 to Country Code exactly. Nonmatching identifiers and missing measurements remain unknown; do not guess them or substitute another year. Retain every original country feature and benchmark_row_id, including unknowns. No data must have a distinct map category, not zero. Create a quantitative choropleth with five quantile classes (fewer only if tied values collapse breaks), a visible legend with numeric bounds and units, and a neutral No data category. Values equal to a class break enter the upper class. Preserve negative and genuine zero values. This fixed classification and year are disclosed evaluation conventions; do not retrieve live replacements.



Add the resulting quantitative country layer to the map and retain an inspectable data artifact containing the original country geometry, benchmark_row_id, numeric value and class. End with one fenced JSON object: {count: countries with a known numeric value, unknown_count: countries without one, coverage_note: string, selection: {collectionId, itemId, assetKey}, value_field: numeric_column_name, class_field: classification_column_name, map_layer_id: delivered_layer_id}. The artifact must include known AND unknown countries, not only the known subset. Explain the year, units, key limitations and legend in the final response.

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": "World Bank country boundaries",
    "edition": "GeoBenchX harmonized names",
    "units": {},
    "collectionId": "blue-generated--[resource id withheld]",
    "itemId": "[resource id withheld]",
    "assetKey": "data"
  },
  {
    "name": "World Bank SP.POP.TOTL",
    "edition": "Frozen GeoBenchX World Development Indicators; use 2023",
    "units": {
      "2023": "people"
    },
    "collectionId": "blue-generated--[resource id withheld]",
    "itemId": "[resource id withheld]",
    "assetKey": "data"
  }
]

Outcome & verification

Independent artifact and delivery checks passed.

Duration
13m 26s
Recorded Blue tool calls
59
Total tokens
2,052,867
Model cost
Not recorded
Application revision
d50497ea9084f29c91b05406688f87035df98d8a
Release
terra-geobenchx-v1

Recorded final answer

Done — the **Country population choropleth** layer is on the map. It uses the supplied frozen **World Bank SP.POP.TOTL 2023** country totals, in **people**, joined by exact **ISO_A3 → Country Code**. I found **217** countries with known values and **34** shown as **No data**. Legend: **No data** plus five quantile classes, with breaks at **466,223.4**, **4,035,963.2**, **11,002,753.2**, and **34,343,880.2** people. Values on a break go in the upper class. Limit: unmatched codes or missing 2023 values stay **No data**, and this is a **country-total** map, not a subnational surface or a new regional aggregation. Next: click a country in the layer to inspect its **benchmark_row_id**, **2023** value, and **population_class**. Source: supplied frozen **World Bank country boundaries** and frozen **World Bank SP.POP.TOTL 2023** table, Blue-hosted GeoBenchX fixtures, retrieved **2026-10-07**. ### Limitations - This map uses the supplied frozen country polygons and the supplied World Bank SP.POP.TOTL 2023 values only. - Unmatched ISO_A3/Country Code pairs and missing 2023 values remain No data. - Values are country totals in people, not a subnational surface or a new regional aggregation. - 34 country features remain No data because the exact ISO_A3 to Country Code join did not produce a numeric 2023 value for them. - Values are country totals in people, not a subnational population surface or a new regional aggregation. - The result uses the supplied frozen country boundaries only. - Nonmatching identifiers and missing 2023 values remain unknown; they are not guessed or replaced. - Repeated quantiles can reduce the number of numeric classes, though the tested output kept five numeric classes plus No data. - The final layer must use the derived classified output rather than the raw inputs.

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
217
Reported count
217
Computation verified
Yes
Answer fulfilled
Yes
Full grading and rubric record
{
  "expectedCount": 217,
  "actualCount": 217,
  "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

Does an exact left join from ISO_A3 to Country Code preserve every supplied country polygon and benchmark_row_id while attaching the frozen SP.POP.TOTL 2023 value where available, and does quantile classification produce the requested quantitative choropleth with a separate No data category?

assess_trial · completed · assessment: sufficient

The full-world private trial preserved all 251 supplied country features and benchmark_row_id values after a left join from ISO_A3 to Country Code. It attached the frozen 2023 SP.POP.TOTL value in people where exact codes matched and left 34 countries with unknown values. The classifier retained all 251 features, created a population_class field with classes 1 through 5 for known values and class 0 for No data, and kept zeros/nonmissing values distinct from unknowns.

assess_result · completed · assessment: sufficient

The final delivered country choropleth matches the tested world-scale computation and preserves all 251 original country features. It joins the supplied frozen World Bank SP.POP.TOTL 2023 values in people by exact ISO_A3 to Country Code matching, keeps 217 countries with known numeric values, and leaves 34 as No data where the exact join did not produce a numeric 2023 value. The final artifact includes geometry, benchmark_row_id, the numeric 2023 field, and population_class, and the map layer is bound to that derived artifact. The legend uses five quantile classes plus a separate No data category, with break-equal values entering the upper class.

Recorded workflow

  1. 01

    Classify country population values

    Recorded vector-classify · succeeded

  2. 02

    Supplied country boundaries

    Recorded source · succeeded

  3. 03

    Country population choropleth

    Recorded output · succeeded

  4. 04

    Join 2023 population to countries

    Recorded table-attribute-join · succeeded

  5. 05

    Supplied frozen World Bank population table

    Recorded source · succeeded

  6. 06

    Classify country population values

    Recorded vector-classify · succeeded

  7. 07

    Supplied country boundaries

    Recorded source · succeeded

  8. 08

    Join 2023 population to countries

    Recorded table-attribute-join · succeeded

  9. 09

    Supplied frozen World Bank population table

    Recorded source · succeeded

  10. 10

    Join 2023 population to countries

    Recorded output · succeeded

  11. 11

    Classify country population values

    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 build this from the supplied frozen country polygons and frozen 2023 World Bank totals, test the exact join and quantile classification on a private draft, then save and run the map-ready workflow. The main limitation is that any ISO_A3/Country Code mismatch or missing 2023 value must stay unknown rather than being filled.

  2. Progress update

    I’m checking the saved analysis context and the exact schemas of the two supplied frozen inputs now. The practical goal is simple: keep every original country polygon, attach the 2023 total-population value where the ISO codes match exactly, and leave the rest as unknown.

  3. get_analysis

    Recorded tool call · completed

  4. get_map_context

    Recorded tool call · completed

  5. get_collection

    Recorded tool call · completed

  6. get_collection

    Recorded tool call · completed

  7. update_analysis_brief

    Recorded tool call · completed

  8. get_item

    Recorded tool call · completed

  9. get_item

    Recorded tool call · completed

  10. list_processors

    Recorded tool call · completed

  11. Progress update

    I found the two key processors I need: an exact table-to-vector attribute join, and a vector quantile classifier that already handles a real legend and a separate No data class. Next I’m checking their exact schemas so I can test the frozen 2023 join without dropping any country rows.

  12. get_tool_help

    Recorded tool call · completed

  13. describe_processors

    Recorded tool call · completed

  14. describe_processors

    Recorded tool call · completed

  15. get_tool_help

    Recorded tool call · completed

  16. Progress update

    I have the exact boundary columns, the exact table columns, and the two processor contracts. I’m pulling a small amount of workflow schema next so I can save the tested method cleanly after the private check, instead of guessing deliverable fields.

  17. get_tool_help

    Recorded tool call · failed

  18. get_tool_help

    Recorded tool call · failed

  19. get_tool_help

    Recorded tool call · failed

  20. get_tool_help

    Recorded tool call · failed

  21. Progress update

    I expect this private draft to answer two key questions at once: whether the exact ISO_A3 → Country Code left join keeps all 251 country rows, and whether the classifier produces a proper population legend with a separate No data category. If either check fails, I’ll fix the calculation before saving the production workflow.

  22. run_trial

    Recorded tool call · completed

  23. Progress update

    The private draft worked at full world extent, which is better than a local proxy. I’m inspecting the classified draft a bit more before I save it as the production workflow, mainly to confirm the final field names, class counts, and legend-ready class assignments.

  24. inspect_artifact

    Recorded tool call · completed

  25. get_trial_report

    Recorded tool call · completed

  26. get_tool_help

    Recorded tool call · completed

  27. get_tool_help

    Recorded tool call · completed

  28. Progress update

    The tested method is ready to turn into the saved workflow. I’m reading the final workflow schema and the exact class rows now so I can preserve the tested computation, the inspectable output, and the final counts without guessing.

  29. inspect_artifact

    Recorded tool call · completed

  30. get_tool_help

    Recorded tool call · completed

  31. get_tool_help

    Recorded tool call · completed

  32. inspect_artifact

    Recorded tool call · completed

  33. Progress update

    I’ve confirmed the tested draft keeps all 251 country features and already shows 34 unknowns. I’m pulling the exact class rows and the workflow save schema now so I can save the tested method, run the final artifact, and attach the real map layer instead of describing a draft.

  34. get_tool_help

    Recorded tool call · completed

  35. Progress update

    The save schema is available now. I’m reading the exact proposal fields next so I can save the tested join-and-classify method cleanly, with the derived output selected as the final map artifact.

  36. get_tool_help

    Recorded tool call · completed

  37. get_tool_help

    Recorded tool call · completed

  38. get_tool_help

    Recorded tool call · completed

  39. get_tool_help

    Recorded tool call · completed

  40. get_tool_help

    Recorded tool call · completed

  41. get_tool_help

    Recorded tool call · completed

  42. inspect_artifact

    Recorded tool call · completed

  43. Progress update

    The method check is complete. I’m reading the detailed table rows now to lock in the exact known-versus-unknown totals and then I’ll save and run the final workflow.

  44. read_evidence

    Recorded tool call · completed

  45. assess_trial

    Recorded tool call · completed

  46. inspect_artifact

    Recorded tool call · completed

  47. inspect_artifact

    Recorded tool call · completed

  48. inspect_artifact

    Recorded tool call · completed

  49. inspect_artifact

    Recorded tool call · completed

  50. inspect_artifact

    Recorded tool call · completed

  51. inspect_artifact

    Recorded tool call · completed

  52. Progress update

    I’m reading the full inspected table once so I can derive the exact class bounds from the real output, instead of approximating the legend. After that I can save the tested workflow, run it, bind the layer to the map, and finish the result check.

  53. read_evidence

    Recorded tool call · completed

  54. inspect_artifact

    Recorded tool call · completed

  55. inspect_artifact

    Recorded tool call · completed

  56. inspect_artifact

    Recorded tool call · completed

  57. Progress update

    I already have the known and unknown counts. I’m just repeating the class summaries now so I can extract the exact numeric bounds that the final legend shows for each quantile class.

  58. inspect_artifact

    Recorded tool call · completed

  59. inspect_artifact

    Recorded tool call · completed

  60. inspect_artifact

    Recorded tool call · completed

  61. Progress update

    I’ve now verified the exact legend ranges from the tested output. I’m saving that same tested world-scale computation as the production workflow next, with the derived choropleth selected as the final map artifact.

  62. propose_workflow

    Recorded tool call · completed

  63. Progress update

    The production workflow is saved and matches the tested world-scale computation exactly. I’m running that saved workflow now, then I’ll inspect the delivered artifact, add the layer, and record the final answer object from the real output.

  64. execute_workflow

    Recorded tool call · completed

  65. list_map_layers

    Recorded tool call · completed

  66. inspect_workflow_results

    Recorded tool call · completed

  67. get_workflow_run

    Recorded tool call · completed

  68. Progress update

    I have the finished layer ID and the finished derived dataset ID. I’m doing the last verification now: inspect the final artifact fields and the classifier’s summary output, then I’ll record the answer object against that exact map layer and dataset.

  69. inspect_artifact

    Recorded tool call · completed

  70. inspect_artifact

    Recorded tool call · completed

  71. inspect_artifact

    Recorded tool call · completed

  72. Progress update

    I’ve got the classifier summary, including the exact break values and class counts. I’m pulling the final deliverable receipts now so I can attach the finished artifact and map layer to the accepted result.

  73. inspect_artifact

    Recorded tool call · completed

  74. inspect_artifact

    Recorded tool call · completed

  75. assess_result

    Recorded tool call · completed

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