Research/Terra/ 375632
Task evidence / country-choropleth

Map the global distribution of GDP per capita

PassComputational taskUnpublished draft
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The question

375632
Map the global distribution of GDP per capita
Exact submitted task and declared adaptations
Map the global distribution of GDP per capita

Task conventions: Use the frozen country polygons and World Bank NY.GDP.PCAP.CD 2023 column, in current USD per capita. 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": "GDP per capita",
    "edition": "Frozen WDI; current US dollars by year",
    "units": {
      "2023": "current USD per capita",
      "2020": "current USD per capita",
      "2022": "current USD per capita"
    },
    "collectionId": "blue-generated--[resource id withheld]",
    "itemId": "[resource id withheld]",
    "assetKey": "data"
  }
]

Outcome & verification

Independent artifact and delivery checks passed.

Duration
11m 17s
Recorded Blue tool calls
48
Total tokens
1,874,136
Model cost
Not recorded
Application revision
d50497ea9084f29c91b05406688f87035df98d8a
Release
terra-geobenchx-v1

Recorded final answer

Done — the layer **Global GDP per capita by country (2023)** is on your map. It shows **2023 GDP per capita in current USD per capita** by country. The result keeps all **251** supplied country features and benchmark rows. **186** countries have known values, and **65** are **No data**, including **34** exact code nonmatches. The legend uses **five quantile classes** for known values, with breaks at **1,969.87**, **5,344.21**, **12,016.91**, and **32,163.51** current USD per capita, plus a separate **No data** category. Values exactly on a break go into the higher class. Key limits: this is a **country-level** 2023 map only, not a subnational surface or new regional aggregation, and unknown countries were left unknown rather than guessed. Sources: **Benchmark fixture · World Bank country boundaries** (Blue-hosted immutable input from World Bank Official Boundaries, GeoBenchX harmonized names; source revision not provided; retrieved **2026-10-07 UTC**) and **Benchmark fixture · GDP per capita** (Blue-hosted frozen World Bank WDI **NY.GDP.PCAP.CD**; source revision not provided; retrieved **2026-10-07 UTC**). ### Limitations - This is a country-level 2023 indicator in current USD per capita. It is not a subnational surface or a new regional aggregation. - Sixty-five countries remain No data overall because the supplied 2023 value is missing or the exact code join did not match, including 34 exact code nonmatches. - Sixty-five countries remain No data overall because the supplied 2023 measurement is missing or the exact ISO_A3 to Country Code join did not match. That includes 34 exact code nonmatches. - These are the supplied harmonized country boundaries, not live or subnational geometry. - This uses only the supplied World Bank NY.GDP.PCAP.CD 2023 field in current USD per capita. - The tested exact join left 34 countries unmatched by code, and 65 countries have unknown 2023 values overall after the join. - Known values are classified into five quantile classes unless repeated breaks collapse a class. Unknown values remain a separate No data class. - The final output must include known and unknown countries in one derived vector artifact and be added to the current map.

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
186
Reported count
186
Computation verified
Yes
Answer fulfilled
Yes
Full grading and rubric record
{
  "expectedCount": 186,
  "actualCount": 186,
  "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 of country ISO_A3 to GDP Country Code preserve all original countries and produce the required 2023 quantile choropleth with five quantile classes for known values and a distinct No data class for unknowns?

assess_trial · completed · assessment: sufficient

The full-world trial answered the method question. The exact left join of ISO_A3 to Country Code preserved all 251 supplied country features and all 251 benchmark_row_id values. Producer observations reported 217 matched input features and 34 unmatched input features after the left join. The joined 2023 field remained numeric where available and null otherwise, with 65 null 2023 values in the joined output overall. The classification step preserved all 251 features, retained the 2023 numeric field with unit current USD per capita, and added the integer class field gdp_pcap_2023_class. The class field has six distinct values from 0 to 5, which is consistent with a distinct No data class plus five quantile classes for known values.

assess_result · completed · assessment: sufficient

The final deliverable is a single derived country vector artifact that is already on the map. It retains all 251 supplied country features and all benchmark_row_id values, contains the numeric `2023` field and class field `gdp_pcap_2023_class`, and uses current USD per capita. The final artifact has 186 countries with known 2023 GDP per capita values and 65 countries in No data overall. Final join observations report 34 exact code nonmatches. The classifier produced five quantile classes for known values plus class 0 for No data, with class counts {0:65,1:37,2:37,3:37,4:37,5:38}. The legend breaks are 1,969.86648107793, 5,344.21439437871, 12,016.907421906, and 32,163.5114152484 current USD per capita, and break values enter the upper class.

Recorded workflow

  1. 01

    Classify 2023 GDP per capita

    Recorded vector-classify · succeeded

  2. 02

    Supplied country polygons

    Recorded source · succeeded

  3. 03

    Global GDP per capita by country (2023)

    Recorded output · succeeded

  4. 04

    Supplied GDP table

    Recorded source · succeeded

  5. 05

    Join 2023 GDP to countries

    Recorded table-attribute-join · succeeded

  6. 06

    Classify 2023 GDP per capita

    Recorded vector-classify · succeeded

  7. 07

    Supplied country polygons

    Recorded source · succeeded

  8. 08

    Supplied GDP table

    Recorded source · succeeded

  9. 09

    Join 2023 GDP to countries

    Recorded table-attribute-join · succeeded

  10. 10

    Join 2023 GDP to countries

    Recorded output · succeeded

  11. 11

    Classify 2023 GDP per capita

    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’m checking the current analysis state and the exact Blue tools for a country join, fixed 2023 values, and a 5-class choropleth.

  2. Progress update

    I found the main Blue analysis tools. Next I’m checking the supplied country and GDP datasets so I can join the exact fields and test the classification before saving the full workflow.

  3. get_analysis

    Recorded tool call · completed

  4. Progress update

    I’ve recorded the goal as a world country choropleth and I’m now verifying the source schema and the exact processors for join + quantile classes. The practical target is one final country layer with every original feature kept, including unknowns. The main limit so far is that I still need the exact field names and processor inputs from the supplied snapshots.

  5. update_analysis_brief

    Recorded tool call · completed

  6. list_processors

    Recorded tool call · completed

  7. get_collection

    Recorded tool call · completed

  8. get_collection

    Recorded tool call · completed

  9. get_map_context

    Recorded tool call · completed

  10. Progress update

    The source metadata confirms these are immutable supplied snapshots. I’m now reading sample rows and the join/classification processor schemas so the workflow uses the exact field names and preserves unknown countries correctly.

  11. inspect_artifact

    Recorded tool call · failed

  12. describe_processors

    Recorded tool call · completed

  13. inspect_artifact

    Recorded tool call · failed

  14. inspect_artifact

    Recorded tool call · failed

  15. inspect_artifact

    Recorded tool call · failed

  16. Progress update

    I hit a normal prerequisite: direct artifact inspection only works after a source has been materialized through a trial or workflow. I’m switching to the exact item metadata now, which should expose the file profile or the authorized item selection without guessing fields.

  17. get_item

    Recorded tool call · completed

  18. get_item

    Recorded tool call · completed

  19. get_tool_help

    Recorded tool call · completed

  20. get_tool_help

    Recorded tool call · completed

  21. Progress update

    I now have the exact schemas: the country file includes `ISO_A3` and `benchmark_row_id`, and the GDP table includes `Country Code`, `benchmark_row_id`, and a numeric `2023` column in current USD per capita. I’m pulling bounded samples next, then I’ll run a private trial to confirm the exact left join and quantile classes before saving the full workflow.

  22. get_collection

    Recorded tool call · completed

  23. get_collection

    Recorded tool call · completed

  24. get_tool_help

    Recorded tool call · completed

  25. get_tool_help

    Recorded tool call · completed

  26. get_tool_help

    Recorded tool call · completed

  27. get_tool_help

    Recorded tool call · completed

  28. get_tool_help

    Recorded tool call · completed

  29. get_tool_help

    Recorded tool call · completed

  30. Progress update

    I’ve confirmed the exact source fields from the item metadata. I expect a left join on `ISO_A3` = `Country Code` to keep all 251 country polygons, leave unmatched countries as unknown, and then produce 5 quantile classes for the known `2023` values unless tied breakpoints collapse a class. I’m testing that full world computation privately now so I can inspect the real join counts, the class field, and the legend behavior before I save the production workflow.

  31. run_trial

    Recorded tool call · completed

  32. Progress update

    I found the issue: the brief scope was recorded as text strings, so Blue did not treat it as an explicit geographic extent. I’m correcting that now with the observed world-country bounds and refreshing the confirmed field notes before rerunning the trial.

  33. update_analysis_brief

    Recorded tool call · completed

  34. Progress update

    The private test finished successfully. Practical result: the exact left join kept all 251 countries, 217 countries matched GDP rows, 34 had no matching code, and 65 countries end up unknown for the 2023 numeric field. Next I’m checking the trial’s preview and class details so I can confirm the legend and then save the production workflow from this tested method.

  35. inspect_artifact

    Recorded tool call · completed

  36. inspect_artifact

    Recorded tool call · completed

  37. get_trial_report

    Recorded tool call · completed

  38. inspect_artifact

    Recorded tool call · completed

  39. Progress update

    The join test answered the main method question. I’m reading the finished inspection outputs now to confirm the class field and legend details, then I’ll record that assessment and save the production workflow from this tested computation.

  40. inspect_artifact

    Recorded tool call · completed

  41. inspect_artifact

    Recorded tool call · completed

  42. inspect_artifact

    Recorded tool call · completed

  43. assess_trial

    Recorded tool call · completed

  44. Progress update

    The tested method is ready. It kept all 251 countries, preserved `benchmark_row_id`, left 34 countries unmatched on the exact code join, and left 65 countries with unknown 2023 values overall. The classification step added `gdp_pcap_2023_class` with classes 0–5, where 0 is the neutral unknown class and 1–5 are the five quantile classes for known values. I’m recording that assessment and turning this tested computation into the production workflow now.

  45. update_analysis_brief

    Recorded tool call · completed

  46. Progress update

    I’ve got enough evidence to save the final method. Next I’m validating the production workflow with the same tested join and quantile settings, so I can execute the real deliverable instead of relying on the private trial.

  47. get_tool_help

    Recorded tool call · completed

  48. get_tool_help

    Recorded tool call · completed

  49. propose_workflow

    Recorded tool call · completed

  50. execute_workflow

    Recorded tool call · completed

  51. Progress update

    The production workflow validated cleanly and matches the tested method. I’m executing it now, then I’ll inspect the delivered country artifact, add the verified layer to the map, and record the final answer object from the actual output.

  52. Progress update

    The final run finished in the background. I’m inspecting the delivered output now so I can bind the verified country layer to the map and record the final counts from the actual artifact, not the trial.

  53. get_workflow_run

    Recorded tool call · completed

  54. inspect_workflow_results

    Recorded tool call · completed

  55. Progress update

    The final artifact already exists and the workflow attached a map layer. I’m doing the last inspection on that delivered output now: counts, fields, and the actual map layer entry, so I can finish the verified answer object.

  56. list_map_layers

    Recorded tool call · completed

  57. inspect_artifact

    Recorded tool call · completed

  58. inspect_artifact

    Recorded tool call · completed

  59. inspect_workflow_results

    Recorded tool call · completed

  60. Progress update

    I’ve got the final artifact identity and live map layer. I’m pulling the finished artifact inspection and the classifier summary now so I can confirm the known/unknown counts and the legend break ranges before I finalize the result.

  61. inspect_artifact

    Recorded tool call · completed

  62. inspect_artifact

    Recorded tool call · completed

  63. inspect_artifact

    Recorded tool call · completed

  64. assess_result

    Recorded tool call · completed

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