Research/Terra/ 596430
Task evidence / country-choropleth

Compare forest coverage between Amazon basin countries

PassComputational taskUnpublished draft
Download evidence JSON ↓

The question

596430
Compare forest coverage between Amazon basin countries
Exact submitted task and declared adaptations
Compare forest coverage between Amazon basin countries

Task conventions: Use the frozen country polygons and World Bank AG.LND.FRST.ZS 2021 column, in % of land area. 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 in the declared geography and its 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. Count original boundary features, not deduplicated sovereign states; preserve all source rows that meet the declared geography. Country-code sentinels such as -99 remain unmatched. Geography is fixed to original country features with NAME_EN in ["Bolivia", "Brazil", "Colombia", "Ecuador", "Guyana", "Peru", "Suriname", "Venezuela, RB"]; retain all matching source geometries, and no others. Classification is calculated only over this geography. Membership reflects this disclosed benchmark edition, not current organization membership.



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 AG.LND.FRST.ZS",
    "edition": "Frozen GeoBenchX World Development Indicators; use 2021",
    "units": {
      "2021": "% of land area"
    },
    "collectionId": "blue-generated--[resource id withheld]",
    "itemId": "[resource id withheld]",
    "assetKey": "data"
  }
]

Outcome & verification

Independent artifact and delivery checks passed.

Duration
14m 44s
Recorded Blue tool calls
57
Total tokens
2,178,412
Model cost
Not recorded
Application revision
d50497ea9084f29c91b05406688f87035df98d8a
Release
terra-geobenchx-v1

Recorded final answer

I added the 2021 forest-coverage choropleth to your map. All 8 benchmark country features matched the frozen World Bank value, so the No data class is available but unused in this subset. Legend (% of land area, quantiles): 46.73–<50.98, 50.98–<52.97, 52.97–<56.95, 56.95–<79.81, and 79.81–97.33. Break values go into the upper class. Highest values are Suriname (97.33) and Guyana (93.50); lowest are Bolivia (46.73) and Ecuador (50.06). Limitation: this is a country-level 2021 indicator, not a subnational forest map, and country membership follows the supplied GeoBenchX benchmark boundary edition. Sources: World Bank country boundaries (GeoBenchX harmonized names) and frozen World Bank AG.LND.FRST.ZS 2021 snapshot, retrieved 2026-10-07. Click the map layer to inspect each country’s benchmark row, 2021 value, and class. ### Limitations - This is a frozen 2021 country-level indicator in percent of land area, not a subnational forest surface or a live replacement. - Country membership and retained rows follow the supplied GeoBenchX benchmark boundary edition. - This is a 2021 country-level comparison in percent of land area, not a subnational forest surface. - The No data category remains part of the legend method, but none of the 8 selected benchmark country rows was unknown after the exact join. - This summary reflects the supplied benchmark edition and the frozen 2021 indicator only. - The comparison is country-level only, not a subnational forest map. - Membership and retained rows follow the supplied benchmark boundary edition, and original matching rows are preserved rather than deduplicated. - The join uses ISO_A3 = Country Code exactly and would leave nonmatching codes unknown rather than guessing them. - The result uses the supplied frozen 2021 country indicator in % of land area only; it is not a subnational forest surface or a newer year. - The classifier keeps a neutral No data class for unknowns; this fixed benchmark subset had no unknown rows, so all five numeric classes were used. - The final map must bind to the derived classified artifact rather than either supplied input.

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
8
Reported count
8
Computation verified
Yes
Answer fulfilled
Yes
Full grading and rubric record
{
  "expectedCount": 8,
  "actualCount": 8,
  "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 frozen boundary and indicator snapshots expose the exact fields needed for the required NAME_EN filter, ISO_A3 to Country Code join, benchmark_row_id retention, and 2021 forest percentage value?

assess_trial · completed · assessment: sufficient

The supplied boundary snapshot exposes NAME_EN, ISO_A3, and benchmark_row_id. The supplied indicator table exposes Country Code and a numeric 2021 field, so the required exact key join and fixed-year value are available from the frozen inputs.

run_trial · completed

When I filter the supplied boundary rows to the eight named Amazon-basin countries, join ISO_A3 to Country Code exactly, and classify the 2021 forest percentages into five quantiles, does the output preserve every selected benchmark row, keep unmatched values unknown, and produce the required choropleth classes only over that fixed geography?

assess_trial · completed · assessment: sufficient

The fixed NAME_EN filter retained exactly 8 benchmark country rows: Bolivia, Brazil, Colombia, Ecuador, Guyana, Peru, Suriname, and Venezuela, RB. The exact left join from ISO_A3 to Country Code matched all 8 rows and left 0 unknowns in this benchmark subset. The classifier used the frozen 2021 field, produced 5 quantile classes, and the summary reported breaks at 50.976702889519984, 52.96987283080132, 56.952563812048936, and 79.81021750151093 % of land area.

assess_result · completed · assessment: sufficient

The final published summary reports the frozen 2021 field in % of land area, with 8 known country values and 0 unknowns from the final derived artifact for the fixed benchmark geography. The final delivered layer is country-level only and uses the supplied benchmark country rows.

assess_result · completed · assessment: sufficient

The final published choropleth keeps exactly the 8 benchmark country features for Bolivia, Brazil, Colombia, Ecuador, Guyana, Peru, Suriname, and Venezuela, RB. It retains benchmark_row_id and geometry on every row, joins the frozen World Bank 2021 field by exact ISO_A3 = Country Code with 0 unmatched rows in this subset, and applies five quantile classes over this fixed geography. The delivered map layer is available on the current map as 'Amazon basin forest coverage 2021'.

Recorded workflow

  1. 01

    Filter benchmark Amazon countries

    Recorded vector-filter · succeeded

  2. 02

    Classify 2021 forest percent

    Recorded vector-classify · succeeded

  3. 03

    Benchmark country boundaries

    Recorded source · succeeded

  4. 04

    Amazon basin forest coverage 2021

    Recorded output · succeeded

  5. 05

    Amazon basin forest coverage legend and counts

    Recorded output · succeeded

  6. 06

    Frozen forest indicator table

    Recorded source · succeeded

  7. 07

    Join 2021 forest indicator

    Recorded table-attribute-join · succeeded

  8. 08

    Filter benchmark Amazon countries

    Recorded vector-filter · succeeded

  9. 09

    Classify 2021 forest percent

    Recorded vector-classify · succeeded

  10. 10

    Benchmark country boundaries

    Recorded source · succeeded

  11. 11

    Frozen forest indicator table

    Recorded source · succeeded

  12. 12

    Join 2021 forest indicator

    Recorded table-attribute-join · succeeded

  13. 13

    Join 2021 forest indicator

    Recorded output · succeeded

  14. 14

    Classify 2021 forest percent

    Recorded output · succeeded

  15. 15

    Benchmark country boundaries

    Recorded source · succeeded

  16. 16

    Frozen forest indicator table

    Recorded source · succeeded

  17. 17

    Benchmark country boundaries

    Recorded output · succeeded

  18. 18

    Frozen forest indicator 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 inspect the supplied boundary and indicator tables first, then test the exact join and class logic on this fixed country set before I build the final map layer.

  2. get_analysis

    Recorded tool call · completed

  3. Progress update

    I found no retained work for this request. Next I’m checking the exact fields and authorized item selections in the two supplied frozen inputs so I can use the required 2021 value and preserve every benchmark country row.

  4. get_collection

    Recorded tool call · completed

  5. get_collection

    Recorded tool call · completed

  6. list_items

    Recorded tool call · completed

  7. list_items

    Recorded tool call · completed

  8. inspect_artifact

    Recorded tool call · failed

  9. inspect_artifact

    Recorded tool call · failed

  10. get_tool_help

    Recorded tool call · completed

  11. list_processors

    Recorded tool call · completed

  12. list_processors

    Recorded tool call · completed

  13. update_analysis_brief

    Recorded tool call · completed

  14. Progress update

    I have the fixed inputs recorded now. Next I’m checking the exact processor contracts for filtering, joining, and quantile classification so the trial uses the benchmark rows and the required No data handling exactly.

  15. describe_processors

    Recorded tool call · completed

  16. describe_processors

    Recorded tool call · completed

  17. get_tool_help

    Recorded tool call · completed

  18. get_tool_help

    Recorded tool call · completed

  19. get_tool_help

    Recorded tool call · completed

  20. Progress update

    The main uncertainty now is the exact table column names on the frozen inputs. I expect the boundary file to expose NAME_EN, ISO_A3, and benchmark_row_id, and the indicator table to expose Country Code plus a 2021 value column. I’m running a tiny source-only trial to confirm that before I lock the join and legend fields.

  21. Progress update

    That was just an argument mistake. I’m correcting the trial shape and rerunning the same source check.

  22. run_trial

    Recorded tool call · completed

  23. Progress update

    The source check finished in the background. It confirms the boundary snapshot has NAME_EN, ISO_A3, and benchmark_row_id, and the indicator table has Country Code plus year columns. I still need to confirm the exact 2021 field and then test the full join-and-classify output on the fixed eight-country geography.

  24. inspect_artifact

    Recorded tool call · completed

  25. inspect_artifact

    Recorded tool call · completed

  26. Progress update

    The field checks are ready now. I’m reading the exact sample rows so I can lock the 2021 value column, then I’ll run the full fixed-country join and quantile-classification test.

  27. inspect_artifact

    Recorded tool call · completed

  28. inspect_artifact

    Recorded tool call · completed

  29. Progress update

    The key fields are confirmed now: the boundary file has NAME_EN, ISO_A3, and benchmark_row_id, and the indicator table has Country Code plus a numeric 2021 column. I’m saving that field check, then I’ll run the real eight-country join-and-legend test so I can verify the counts, unknown handling, and class breaks before delivery.

  30. assess_trial

    Recorded tool call · completed

  31. get_tool_help

    Recorded tool call · completed

  32. get_tool_help

    Recorded tool call · completed

  33. get_tool_help

    Recorded tool call · completed

  34. get_tool_help

    Recorded tool call · completed

  35. get_tool_help

    Recorded tool call · completed

  36. get_tool_help

    Recorded tool call · completed

  37. Progress update

    The next check is the real one: I expect the exact NAME_EN filter to keep only the benchmark rows for the eight named countries, the left join to keep every one of those rows even if a code does not match, and the quantile step to classify only the retained geography while leaving unknown values in a separate No data class.

  38. run_trial

    Recorded tool call · completed

  39. Progress update

    I’ve already confirmed the full eight-country test keeps exactly 8 benchmark rows, matches all 8 codes, and produces class values 1–5 with no unknowns in this fixed benchmark set. Next I’m pulling the actual class ranges from the classifier output, then I’ll save the tested method as the final workflow, run it, add the verified layer to the map, and record the result object.

  40. inspect_artifact

    Recorded tool call · completed

  41. describe_processors

    Recorded tool call · completed

  42. get_trial_report

    Recorded tool call · completed

  43. inspect_workflow_results

    Recorded tool call · completed

  44. inspect_artifact

    Recorded tool call · completed

  45. Progress update

    I have the successful trial run already. I’m reading the final country rows and the classifier summary now so I can confirm the exact country values and legend breaks before I save the production workflow.

  46. Progress update

    I’ve confirmed the tested method works on the full fixed country set. Before I publish the final result, I’m checking the layer-binding path and the classifier summary so the map shows the verified derived output with the right legend.

  47. get_tool_help

    Recorded tool call · completed

  48. get_tool_help

    Recorded tool call · completed

  49. get_tool_help

    Recorded tool call · completed

  50. inspect_artifact

    Recorded tool call · completed

  51. inspect_artifact

    Recorded tool call · completed

  52. list_processor_jobs

    Recorded tool call · completed

  53. Progress update

    I’ve got the successful test outputs. I’m pulling the classifier rows and summary, plus the exact processor job IDs, so I can bind the final derived layer to the map and quote the legend ranges from the processor rather than guessing them.

  54. get_tool_help

    Recorded tool call · completed

  55. get_tool_help

    Recorded tool call · completed

  56. get_tool_help

    Recorded tool call · completed

  57. Progress update

    I have the exact class breaks now from the classifier summary. Next I’m validating the final publication path: save the tested workflow, execute it, and bind the final classified output to the map with the authoritative layer receipt.

  58. get_tool_help

    Recorded tool call · completed

  59. get_tool_help

    Recorded tool call · completed

  60. Progress update

    The method is tested now: 8 fixed benchmark country rows, 8 exact code matches, five quantile classes, and no unknowns in this subset. I’m saving that tested method as the final workflow next so I can publish the verified artifact and layer instead of relying on a private trial.

  61. assess_trial

    Recorded tool call · completed

  62. propose_workflow

    Recorded tool call · completed

  63. Progress update

    The saved workflow is ready and matches the tested computation. I’m starting that exact final run now, then I’ll inspect the published outputs and confirm the map binding before I give you the result.

  64. execute_workflow

    Recorded tool call · completed

  65. Progress update

    The approved final run already finished in the background. I’m inspecting its published outputs now, then I’ll bind the final classified layer to the map and record the accepted answer object from that exact final artifact.

  66. inspect_workflow_results

    Recorded tool call · completed

  67. inspect_artifact

    Recorded tool call · completed

  68. inspect_artifact

    Recorded tool call · completed

  69. Progress update

    The final published layer is already on the map. I’m reading the current published rows and the delivered legend summary now so the accepted answer uses the exact final artifact IDs, class field, counts, and map layer ID.

  70. inspect_artifact

    Recorded tool call · completed

  71. inspect_artifact

    Recorded tool call · completed

  72. Progress update

    The final map layer is already bound. I’m doing one last read of the published country rows from the delivered layer itself, then I’ll record the final accepted result with the exact artifact IDs and layer ID.

  73. list_map_layers

    Recorded tool call · completed

  74. inspect_artifact

    Recorded tool call · completed

  75. assess_result

    Recorded tool call · completed

  76. Progress update

    I’ve verified the final published outputs and the live map layer. I’m recording the summary assessment first, then the map result with the exact artifact selection and layer ID for the accepted final answer.

  77. assess_result

    Recorded tool call · completed

|||

© 2026 Exia Labs, Inc.