Research/Terra/ 250712
Task evidence / country-choropleth

Visualize net migration patterns worldwide

PassComputational taskUnpublished draft
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The question

250712
Visualize net migration patterns worldwide.
Exact submitted task and declared adaptations
Visualize net migration patterns worldwide. 

Task conventions: Use the frozen country polygons and World Bank SM.POP.NETM 2023 column, in people (net migration). 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": "Net migration, World Development Indicators",
    "edition": "2024-11-13 snapshot; use 2023",
    "units": {
      "2023": "people (net migration)"
    },
    "collectionId": "blue-generated--[resource id withheld]",
    "itemId": "[resource id withheld]",
    "assetKey": "data"
  }
]

Outcome & verification

Independent artifact and delivery checks passed.

Duration
17m 45s
Recorded Blue tool calls
58
Total tokens
2,326,112
Model cost
Not recorded
Application revision
d50497ea9084f29c91b05406688f87035df98d8a
Release
terra-geobenchx-v1

Recorded final answer

Done — the worldwide 2023 net migration country layer is on your map. It uses the supplied World Bank SM.POP.NETM 2023 values in people, joined exactly from `ISO_A3` to `Country Code`, with five quantile classes and a separate No data class. The legend breaks are -15,237.4, -3,173.4, -21.6, and 3,950.0 people. I mapped 217 countries with known values and kept 34 country features as No data. Important limit: this is a country-level 2023 view only, not a subnational surface or a new regional aggregation. Next: click the layer to inspect each country’s value, class, and `benchmark_row_id`. Source: supplied World Bank country boundaries and supplied archived World Bank WDI net migration snapshot, retrieved 2026-10-07. ### Limitations - This is a country-level 2023 indicator map, not a subnational surface or a new regional aggregation. - Exact ISO_A3 to Country Code matching leaves 34 country features without a known 2023 value, so they remain No data. - 34 country features remain No data under the exact ISO_A3 to Country Code join. - Quantile thresholds are distribution-based class bounds and appear as decimal break values even though the source values are country counts in people. - All 251 supplied country features are retained in the final artifact. - Uses only the supplied 2023 snapshot and does not substitute another year. - 34 country features remain unknown because exact identifiers do not match or no 2023 value is available. - The final map is country-level only, not a subnational surface or a new regional aggregation.

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

Do the supplied source files expose the exact fields needed for the required join and final artifact?

assess_trial · completed · assessment: sufficient

The supplied country boundary file exposes ISO_A3 and benchmark_row_id. The supplied indicator table exposes Country Code and a numeric 2023 field for SM.POP.NETM. My earlier expectation that the indicator table also needed benchmark_row_id was incorrect; the task only requires retaining benchmark_row_id from the original country features, so the available fields are sufficient for the required exact join and final artifact.

run_trial · completed

Does an exact global left join from ISO_A3 to Country Code retain every supplied country feature and produce the required 2023 net migration quantile choropleth with unknown countries kept as No data?

assess_trial · completed · assessment: sufficient

The exact global left join retained all 251 supplied country features and their benchmark_row_id values. It produced 217 countries with a known numeric 2023 value and 34 countries with unknown 2023 after exact ISO_A3 to Country Code matching. The classified output retained all 251 features, used five quantile classes for known values, kept unknown countries in class 0, and preserved genuine zero values as data rather than No data. The generated summary reported breaks at -15237.4, -3173.4, -21.6, and 3950.0 people, with class counts 34 No data, then 44, 43, 43, 43, and 44 across classes 1 to 5.

assess_result · completed · assessment: sufficient

The worldwide 2023 net migration choropleth is on the map as layer `Country net migration 2023` (layer `[resource id withheld]`). The delivered artifact retains all 251 supplied country features and benchmark_row_id values, with 217 known 2023 net migration values and 34 No data features after the exact ISO_A3 to Country Code join. The delivered summary reports five quantile classes for known values with breaks at -15237.4, -3173.4, -21.6, and 3950.0 people (net migration), plus class 0 for No data. Genuine zero values remain valid data and are not mapped as No data. Sources: Benchmark fixture · World Bank country boundaries (provider: Blue; immutable supplied input; retrieved 2026-10-07) and Benchmark fixture · Net migration, World Development Indicators, 2024-11-13 snapshot using 2023 (provider: Blue hosting archived World Bank WDI input; retrieved 2026-10-07).

Recorded workflow

  1. 01

    Quantile choropleth for 2023 net migration

    Recorded vector-classify · succeeded

  2. 02

    Supplied country polygons

    Recorded source · succeeded

  3. 03

    Country net migration 2023

    Recorded output · succeeded

  4. 04

    Join 2023 net migration to countries

    Recorded table-attribute-join · succeeded

  5. 05

    Supplied net migration table

    Recorded source · succeeded

  6. 06

    Quantile choropleth for 2023 net migration

    Recorded vector-classify · succeeded

  7. 07

    Supplied country polygons

    Recorded source · succeeded

  8. 08

    Join 2023 net migration to countries

    Recorded table-attribute-join · succeeded

  9. 09

    Supplied net migration table

    Recorded source · succeeded

  10. 10

    Join 2023 net migration to countries

    Recorded output · succeeded

  11. 11

    Quantile choropleth for 2023 net migration

    Recorded output · succeeded

  12. 12

    Quantile choropleth for 2023 net migration

    Recorded output · succeeded

  13. 13

    Supplied country polygons

    Recorded source · succeeded

  14. 14

    Supplied migration table

    Recorded source · succeeded

  15. 15

    Supplied country polygons

    Recorded output · succeeded

  16. 16

    Supplied migration 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’m checking the retained analysis and the supplied country and indicator data first, then I’ll test the exact join and five-quantile choropleth method before building the final map layer.

  2. get_collection

    Recorded tool call · completed

  3. get_analysis

    Recorded tool call · completed

  4. get_collection

    Recorded tool call · completed

  5. Progress update

    I found the two supplied immutable inputs. Next I’m inspecting their actual fields and a small sample so I can join `ISO_A3` to `Country Code` exactly, keep all countries, and classify only the 2023 numeric values.

  6. get_collection

    Recorded tool call · completed

  7. get_collection

    Recorded tool call · completed

  8. list_processors

    Recorded tool call · completed

  9. list_processors

    Recorded tool call · completed

  10. list_processors

    Recorded tool call · completed

  11. describe_processors

    Recorded tool call · completed

  12. describe_processors

    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. get_tool_help

    Recorded tool call · completed

  17. get_tool_help

    Recorded tool call · completed

  18. Progress update

    I’ve identified the two processors I need: a left attribute join and a quantitative vector classifier. The remaining uncertainty is the exact field names and whether the join keeps every country with unknowns preserved, so I’m setting up a small private trial that reaches the final country choropleth output and will inspect the joined rows and classing result directly.

  19. update_analysis_brief

    Recorded tool call · completed

  20. run_trial

    Recorded tool call · completed

  21. Progress update

    The first inspection succeeded. I confirmed the boundary file has `ISO_A3` and `benchmark_row_id`, and the indicator file has `Country Code` plus yearly numeric fields. I’m now checking the exact 2023 column name and then I’ll run one end-to-end trial of the exact left join and quantile choropleth before saving the final workflow.

  22. inspect_artifact

    Recorded tool call · completed

  23. get_trial_report

    Recorded tool call · completed

  24. inspect_artifact

    Recorded tool call · completed

  25. Progress update

    The source check is already useful: the boundary file has `ISO_A3`, and the indicator file has `Country Code` and yearly fields through 2019 in the summary, so I’m verifying the exact 2023 column directly from the inspected schema and sample rows before I join and classify.

  26. inspect_artifact

    Recorded tool call · completed

  27. inspect_artifact

    Recorded tool call · completed

  28. inspect_artifact

    Recorded tool call · completed

  29. Progress update

    I confirmed the indicator schema includes a `2023` numeric field. One sample-row request failed because I asked for `benchmark_row_id` on the indicator table, which it does not have. That is not a data gap for this task, because only the original country features need their `benchmark_row_id` retained. I’m correcting that field request now, then I’ll run the exact left join and quantile classification trial.

  30. inspect_artifact

    Recorded tool call · completed

  31. inspect_artifact

    Recorded tool call · completed

  32. assess_trial

    Recorded tool call · completed

  33. Progress update

    The schema check is done. I’ve corrected the mistaken field request, and I’m pulling a few indicator rows now so I can confirm the 2023 values before running the full worldwide join-and-classify test.

  34. inspect_artifact

    Recorded tool call · completed

  35. run_trial

    Recorded tool call · completed

  36. get_tool_help

    Recorded tool call · completed

  37. inspect_artifact

    Recorded tool call · completed

  38. inspect_artifact

    Recorded tool call · completed

  39. inspect_artifact

    Recorded tool call · completed

  40. get_tool_help

    Recorded tool call · completed

  41. get_tool_help

    Recorded tool call · completed

  42. Progress update

    The full trial already shows the key result: all 251 country features were retained, 217 have known 2023 values, and 34 stayed unknown. I’m doing one last spot-check on unknown and zero rows, then I’ll save and run the final map workflow so I can add the verified choropleth layer to your map.

  43. inspect_artifact

    Recorded tool call · completed

  44. inspect_artifact

    Recorded tool call · completed

  45. inspect_artifact

    Recorded tool call · completed

  46. get_tool_help

    Recorded tool call · completed

  47. get_tool_help

    Recorded tool call · completed

  48. Progress update

    I’ve confirmed the key edge cases too: the final trial kept 34 unknown countries in class `0` as No data, and genuine `2023 = 0` countries were kept as data in class `4`, not No data. I’m pulling the classified preview and the proposal schema now so I can save the tested method exactly and publish the final layer.

  49. Progress update

    The global choropleth preview is ready and the spot checks passed: 251 total country features, 217 known values, 34 No data, and valid zero values stayed in an ordinary quantile class. I’m now saving the tested workflow exactly, then I’ll execute it and add the verified layer to the map.

  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. update_analysis_brief

    Recorded tool call · completed

  54. assess_trial

    Recorded tool call · completed

  55. Progress update

    The tested method is ready to save exactly as the final workflow: exact left join on the fixed codes, one 2023 value field, five quantile classes, and a separate No data class. I’m saving that now with the current limitations so I can run it unchanged and add the final layer.

  56. propose_workflow

    Recorded tool call · completed

  57. execute_workflow

    Recorded tool call · completed

  58. Progress update

    The final workflow is saved and validated against the tested computation with no blocking issues. I’m executing that unchanged workflow now, then I’ll inspect its delivered artifact, add the verified choropleth layer to your map, and record the final answer object.

  59. inspect_workflow_results

    Recorded tool call · completed

  60. list_map_layers

    Recorded tool call · completed

  61. Progress update

    The saved workflow appears to have completed, so I’m inspecting its delivered output directly now. After that I’ll bind the verified country layer to the map and record the final result with the exact delivered artifact.

  62. inspect_artifact

    Recorded tool call · completed

  63. inspect_artifact

    Recorded tool call · completed

  64. inspect_artifact

    Recorded tool call · completed

  65. inspect_artifact

    Recorded tool call · completed

  66. inspect_artifact

    Recorded tool call · completed

  67. inspect_artifact

    Recorded tool call · completed

  68. Progress update

    I’ve already confirmed the final map layer and the delivered counts. I’m retrieving the last zero-value row receipt and the final-assessment schema now so I can record the exact answer object on the delivered artifact rather than a draft.

  69. get_tool_help

    Recorded tool call · completed

  70. get_tool_help

    Recorded tool call · completed

  71. inspect_artifact

    Recorded tool call · completed

  72. Progress update

    I have the delivered artifact, the delivered summary, the final map layer ID, and the edge-case checks for unknowns and genuine zeros. I’m recording the final result now against the actual delivered layer and artifact.

  73. assess_result

    Recorded tool call · completed

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