Research/Terra/ 631643
Task evidence / bivariate-map

Make a map visualizing relationship between fertility rate and net migration (normalized by total population) across the World.

FailComputational taskUnpublished draft
Download evidence JSON ↓

The question

631643
Make a map visualizing relationship between fertility rate and net migration (normalized by total population) across the World.
Exact submitted task and declared adaptations
Make a map visualizing relationship between fertility rate and net migration (normalized by total population) across the World.

Task conventions: Use the frozen country boundaries and the 2022 column of every supplied indicator. X is fertility (births per woman); Y is migration (net migrants per person). Y is net migration divided by total population, NOT multiplied by 100 or 1000. Join ISO_A3 to Country Code exactly. Keep every original country feature and benchmark_row_id, including unknowns and repeated country identities. Do not guess missing values or substitute years. A missing numerator or missing/zero denominator is unknown. Make one bivariate choropleth: three quantile classes on each axis, computed over rows where BOTH measurements are known. Collapse tied breaks; equality enters the upper class. Combined class is (yClass-1)*xClasses+xClass with 1-based axes. Missing either measurement is neutral class zero. Retain the numeric X and Y values even when only one is missing. The legend must distinguish joint classes with both ranges and units. These are disclosed evaluation conventions, not live-data replacements or proof of causation.



Add the quantitative joint-class layer to the map and retain its complete vector artifact. End with one fenced JSON object: {count: rows with both measurements known, unknown_count: rows missing either, coverage_note: string, selection: {collectionId,itemId,assetKey}, value_field: X numeric column, y_value_field: Y numeric column, class_field: joint class column, map_layer_id: delivered layer ID}. Explain year, units, missing coverage and the relationship without claiming causality.

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": "Fertility rate",
    "edition": "Frozen WDI; use 2022",
    "units": {
      "2022": "births per woman"
    },
    "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"
  },
  {
    "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

Artifact measurement values differ from the frozen source calculation.

Duration
23m 20s
Recorded Blue tool calls
65
Total tokens
2,626,636
Model cost
Not recorded
Application revision
d50497ea9084f29c91b05406688f87035df98d8a
Release
terra-geobenchx-v1

Recorded final answer

Done — the bivariate country layer is on the map and the retained final vector artifact is selected. It uses fertility 2022 on X in births per woman, and 2023 net migration divided by 2023 population on Y in net migrants per person. 210 country features have both values known; 41 are neutral class 0 because one or both values are unknown after the exact ISO_A3-to-Country Code join. The pattern is descriptive only and does not show causality. ### Limitations - The map is descriptive only. It shows how countries fall into joint classes in these supplied snapshots, not causation. - Countries with missing fertility, missing net migration, or missing or zero population remain unknown and use neutral class 0. - The relationship is descriptive only and does not show causality. - 41 of 251 country features are neutral class 0 because fertility or normalized migration is unknown after the required exact join. - 34 exact ISO_A3 codes remain unmatched in at least one indicator join, and repeated country identities remain repeated. - Repeated country identities stay repeated. - Exact unmatched codes remain unknown rather than being repaired. - 41 country features have no fertility value after the required exact join and stay neutral-class unknowns. - 34 country features have unknown Y after the required exact join because the numerator or denominator is unavailable through that key. - The class boundaries summarize these supplied snapshots only and do not imply causation.

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
210
Reported count
210
Computation verified
No
Answer fulfilled
No
Full grading and rubric record
{
  "expectedCount": 210,
  "actualCount": 210,
  "expectedMetrics": null,
  "actualMetrics": null,
  "computationCorrect": false,
  "answerFulfilled": false,
  "adjudication": null,
  "qualification": null,
  "reasons": [
    "Artifact measurement values differ from the frozen source calculation."
  ]
}

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 aliased year fields, exact ISO_A3-to-Country Code left joins, net migration normalization, and 3x3 quantile bivariate classification produce a full-world country artifact that preserves every boundary feature, keeps numeric X and Y values, and assigns neutral class 0 to unknowns?

assess_trial · completed · assessment: sufficient

The full-world trial succeeded with the exact supplied sources and years. Left joins preserved all 251 boundary features and benchmark_row_id values. The joined output kept 217 matched migration/population rows and 217 computed net_mig_per_person values; 34 rows stayed unknown because the exact ISO_A3-to-Country Code join left them unmatched. The classifier used 210 paired known rows, produced 3 x-axis classes and 3 y-axis classes, and assigned neutral class 0 to 41 rows where either value was unknown. The class summary reports xBreaks 1.65 and 2.711 births per woman, yBreaks -0.00084714204 and 0 net migrants per person, and the documented code formula (yClass - 1) * xClasses + xClass. Inspection of neutral rows shows numeric net_mig_per_person values were retained for some rows with missing fertility, such as San Marino and Monaco.

assess_result · completed · assessment: sufficient

The final production output matches the tested world method. The selected vector artifact preserves all 251 supplied country features, keeps fertility_2022 in births per woman and net_mig_per_person in net migrants per person, and classifies the 210 countries with both values known into a 3 by 3 quantile bivariate scheme with class 0 for the 41 unknowns. X uses the supplied fertility 2022 snapshot. Y uses the supplied 2023 net migration snapshot divided by the supplied 2023 population snapshot, exactly as computed in the saved workflow. Countries in higher X classes have higher fertility, and countries in higher Y classes have more positive net migration per person relative to the observed breaks, but the map is descriptive only and does not establish causation.

Recorded workflow

  1. 01

    Calculate normalized migration

    Recorded vector-field-calculate · succeeded

  2. 02

    Create bivariate classes

    Recorded vector-bivariate-classify · succeeded

  3. 03

    World fertility and net migration bivariate choropleth

    Recorded output · succeeded

  4. 04

    Alias fertility 2022

    Recorded table-group-statistics · succeeded

  5. 05

    Join fertility

    Recorded table-attribute-join · succeeded

  6. 06

    Join migration

    Recorded table-attribute-join · succeeded

  7. 07

    Join population

    Recorded table-attribute-join · succeeded

  8. 08

    Alias migration 2023

    Recorded table-group-statistics · succeeded

  9. 09

    Alias population 2023

    Recorded table-group-statistics · succeeded

  10. 10

    blue-generated--[resource id withheld]

    Recorded source · succeeded

  11. 11

    blue-generated--[resource id withheld]

    Recorded source · succeeded

  12. 12

    blue-generated--[resource id withheld]

    Recorded source · succeeded

  13. 13

    blue-generated--[resource id withheld]

    Recorded source · succeeded

  14. 14

    Calculate normalized migration

    Recorded vector-field-calculate · succeeded

  15. 15

    Create bivariate classes

    Recorded vector-bivariate-classify · succeeded

  16. 16

    Alias fertility 2022

    Recorded table-group-statistics · succeeded

  17. 17

    Join fertility

    Recorded table-attribute-join · succeeded

  18. 18

    Join migration

    Recorded table-attribute-join · succeeded

  19. 19

    Join population

    Recorded table-attribute-join · succeeded

  20. 20

    Alias migration 2023

    Recorded table-group-statistics · succeeded

  21. 21

    Alias population 2023

    Recorded table-group-statistics · succeeded

  22. 22

    blue-generated--[resource id withheld]

    Recorded source · succeeded

  23. 23

    blue-generated--[resource id withheld]

    Recorded source · succeeded

  24. 24

    blue-generated--[resource id withheld]

    Recorded source · succeeded

  25. 25

    blue-generated--[resource id withheld]

    Recorded source · succeeded

  26. 26

    Join population

    Recorded output · succeeded

  27. 27

    Calculate normalized migration

    Recorded output · succeeded

  28. 28

    Create bivariate classes

    Recorded output · succeeded

  29. 29

    Create bivariate classes

    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 sources first, then build a small tested method for the join, 2022/2023 values, and bivariate classes before I save the full map workflow.

  2. Progress update

    I found the analysis tools. Next I’m checking the saved analysis context and the exact schemas of the four supplied inputs so I can join the right fields without dropping countries.

  3. get_collection

    Recorded tool call · completed

  4. get_analysis

    Recorded tool call · completed

  5. get_collection

    Recorded tool call · completed

  6. get_collection

    Recorded tool call · completed

  7. get_collection

    Recorded tool call · completed

  8. Progress update

    The supplied collections are fixed snapshots. I’ve confirmed the editions. Now I’m reading the actual columns and a few sample rows so I can use the exact join keys and year fields the data really contains.

  9. inspect_artifact

    Recorded tool call · failed

  10. inspect_artifact

    Recorded tool call · failed

  11. inspect_artifact

    Recorded tool call · failed

  12. inspect_artifact

    Recorded tool call · failed

  13. get_item

    Recorded tool call · completed

  14. Progress update

    The direct artifact inspect is not allowed for raw inputs, so I’m switching to item metadata and bounded source inspection instead. That should still expose the exact fields and sample values I need.

  15. get_item

    Recorded tool call · completed

  16. get_item

    Recorded tool call · completed

  17. get_item

    Recorded tool call · completed

  18. Progress update

    I have the exact source columns now: boundaries use `ISO_A3`, indicators use `Country Code`, and all four snapshots include the year columns. Next I’m finding the processors for join, field calculation, and classing.

  19. list_processors

    Recorded tool call · completed

  20. get_tool_help

    Recorded tool call · completed

  21. get_tool_help

    Recorded tool call · completed

  22. get_tool_help

    Recorded tool call · completed

  23. Progress update

    I found a direct bivariate-classify processor, which is a good fit because it already preserves all features, handles neutral class 0 for unknowns, collapses tied quantile breaks, and publishes a legend with ranges and units. I’m checking its exact inputs and the join/calculate schemas before I test the whole chain.

  24. describe_processors

    Recorded tool call · completed

  25. describe_processors

    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. Progress update

    There’s one practical wrinkle: both migration and population use a raw `2023` column name. I need to avoid a field-name collision before I can compute net migrants per person cleanly. I’m checking whether Blue has a table-side rename or join option; otherwise I’ll use a tested workaround.

  30. list_processors

    Recorded tool call · completed

  31. list_processors

    Recorded tool call · completed

  32. describe_processors

    Recorded tool call · completed

  33. describe_processors

    Recorded tool call · completed

  34. describe_processors

    Recorded tool call · completed

  35. Progress update

    I found a better workaround: if the table statistics processor can alias fields, I can rename each raw `2023` column on the table side before joining. That would keep the joins exact and avoid any risky overwrite behavior.

  36. Progress update

    I’m saving the analysis brief now. I’m treating the years named in the immutable inputs as authoritative for the computation: fertility 2022, migration 2023, and population 2023. If the trial shows a problem, I’ll revise before I save the final workflow.

  37. update_analysis_brief

    Recorded tool call · completed

  38. Progress update

    I’ve got a tested path in mind now: alias each indicator’s year field on the table side, left-join them to the frozen countries, compute net migrants per person, then let the bivariate classifier make the joint classes and legend. I’m running that exact chain as a private trial over the whole world because the dataset is small enough that the trial can be representative, not just a toy subset.

  39. Progress update

    The first trial submission had a schema mistake only: `inspect_outputs` belongs at the request level, not inside `computation`. I’m correcting that now and retrying the same test.

  40. run_trial

    Recorded tool call · completed

  41. Progress update

    The private test succeeded. It preserved all 251 country features, kept `benchmark_row_id`, computed normalized migration as a per-person ratio, and produced 3x3 quantile breaks from the 210 countries where both values are known. I’m reading the saved trial report and the proposal schema now so I can turn this tested method into the final map workflow without changing the science.

  42. get_tool_help

    Recorded tool call · completed

  43. get_trial_report

    Recorded tool call · completed

  44. get_tool_help

    Recorded tool call · completed

  45. get_tool_help

    Recorded tool call · completed

  46. Progress update

    I’ve confirmed the tested method and I’m doing one more check on the edge cases: a few rows where the joint class is 0 should still keep the numeric X or Y value that is available. That lets me verify the “keep numeric values even when one side is missing” rule before I save the production workflow.

  47. inspect_artifact

    Recorded tool call · completed

  48. inspect_artifact

    Recorded tool call · completed

  49. get_tool_help

    Recorded tool call · completed

  50. get_tool_help

    Recorded tool call · completed

  51. Progress update

    The method is holding up. I’m finishing the production draft from the tested full-world run, then I’ll publish the map layer and final artifact after one last value check on the neutral class rows.

  52. Progress update

    I’ve got the neutral-class checks queued. While those finish, I’m pulling the workflow contract schema so the saved production draft will document the exact sources, joins, and class method that were tested.

  53. inspect_artifact

    Recorded tool call · completed

  54. inspect_artifact

    Recorded tool call · completed

  55. get_tool_help

    Recorded tool call · completed

  56. get_tool_help

    Recorded tool call · completed

  57. Progress update

    The trial answered the main method question: 210 countries have both measurements known, 41 are neutral-class unknowns, and at least some neutral rows still keep a numeric migration value when fertility is missing. I’m updating the saved brief to remove stale “test this later” notes, then I’ll save the production workflow from this exact tested computation.

  58. assess_trial

    Recorded tool call · completed

  59. get_tool_help

    Recorded tool call · completed

  60. update_analysis_brief

    Recorded tool call · completed

  61. Progress update

    I’ve updated the brief with the tested counts and limitations. Next I’m saving the exact full-world method as the production workflow so I can run the final deliverable without changing sources, years, joins, or class rules.

  62. propose_workflow

    Recorded tool call · completed

  63. execute_workflow

    Recorded tool call · completed

  64. Progress update

    The production draft validated cleanly and matches the tested computation exactly. I’m running that saved workflow now, then I’ll inspect the final artifact, add the layer to the map, and record the final answer object against the delivered output.

  65. Progress update

    The saved workflow has finished. I’m inspecting the final output now so I can bind the delivered vector artifact, add the map layer, and record the final answer against the actual production result rather than the private trial.

  66. inspect_workflow_results

    Recorded tool call · completed

  67. inspect_workflow_results

    Recorded tool call · completed

  68. inspect_artifact

    Recorded tool call · completed

  69. inspect_artifact

    Recorded tool call · completed

  70. Progress update

    I’m verifying the final production artifact against the edge-case rules now: the saved workflow should match the trial, but I still need the final artifact receipt, a couple of neutral-class examples, and the exact layer binding before I can finish.

  71. inspect_artifact

    Recorded tool call · completed

  72. inspect_artifact

    Recorded tool call · completed

  73. inspect_workflow_results

    Recorded tool call · completed

  74. inspect_artifact

    Recorded tool call · completed

  75. list_processor_jobs

    Recorded tool call · completed

  76. inspect_artifact

    Recorded tool call · completed

  77. inspect_artifact

    Recorded tool call · completed

  78. Progress update

    I’ve got the final artifact and class summary. I’m pulling the last neutral-class sample rows now, then I’ll add the bivariate layer to the map and record the final answer object against the delivered production output.

  79. add_result_layer

    Recorded tool call · failed

  80. Progress update

    I’m checking the live map bindings now. If the final layer is already on the map, I’ll reuse that layer ID; otherwise I’ll add the exact saved output item and then finish the result assessment.

  81. inspect_artifact

    Recorded tool call · completed

  82. list_map_layers

    Recorded tool call · completed

  83. get_analysis

    Recorded tool call · completed

  84. get_tool_help

    Recorded tool call · completed

  85. Progress update

    I have the final vector item and the live map layer ID. I’m checking the exact `assess_result` example once so I pass the final artifact references in the format Blue expects, then I’ll record the accepted answer object.

  86. Progress update

    The workflow already exposed a matching map layer, but I’m also adding the exact saved output item directly so the final answer can point to an authoritative layer binding for this vector artifact.

  87. add_catalog_layer

    Recorded tool call · completed

  88. list_map_layers

    Recorded tool call · completed

  89. Progress update

    I’ve added the exact output item to the map and I’m doing one last layer check so the final answer can point to the live delivered layer ID, not just the saved vector item.

  90. assess_result

    Recorded tool call · completed

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