Research/Terra/ 112207
Task evidence / geographic-heatmap

Create a heatmap showing railway station density in areas with high snow accumulation in the USA

PartialComputational taskUnpublished draft
Download evidence JSON ↓

The question

112207
Create a heatmap showing railway station density in areas with high snow accumulation in the USA.
Exact submitted task and declared adaptations
Create a heatmap showing railway station density in areas with high snow accumulation in the USA.

Task conventions: Use the frozen raster to select source points. Select stations whose containing original raster cell has band-1 snowfall strictly greater than 39.37 inches. NoData and off-grid samples are unknown, not zero; no interpolation or reprojection of the source raster. Retain sampled inches as snow_depth and weight by that field, following the archived reference: this is a snowfall-weighted station heatmap, not an unweighted station count. Use original point records and the declared attribute/raster selection; do not infer a separate geographic boundary. Unknown country indicators, nonpositive ratio denominators, missing geometry and missing/nonfinite weights are unknown, not zero. Known zero weights remain valid. Exclude valid points outside the specified geography. Include only eligible points with a finite nonnegative weight in the contributing artifact; report other potentially eligible points as unknown. Use this explicit geographic heatmap convention: grid={"bounds": [-18000000, -7325000, 18000000, 7325000], "crs": "EPSG:6933", "resolutionX": 25000, "resolutionY": 25000}, radius 150000 metres = three Gaussian standard deviations. First bin each point into its containing grid cell and sum its weight. Smooth using a normalized separable Gaussian, numerical support four standard deviations, constant-zero exterior; do not renormalize edges. Use both grid resolutions for the two axes; keep original grid alignment. This is a declared metric raster adaptation to the original interactive screen-pixel heatmap, not an equivalent zoom-dependent rendering. Output unit: sum of inches per grid cell. Zero cells are valid; this is not density per square kilometre. Do not rescale the values for presentation.



Add the heatmap raster to the map and retain an inspectable selected-point artifact with original geometry and benchmark_row_id. End with one fenced JSON object: {count: contributing point records, unknown_count: records with unknown eligibility or weight, unlocated_count: original points lacking valid geometry, coverage_note: string, selection: {collectionId,itemId,assetKey}, density: {collectionId,itemId,assetKey}, map_layer_id: heatmap_layer_id}. Explain the data edition, numerical weights, grid, smoothing and coverage limitations. The source-point artifact is not itself the requested heatmap.

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": "Amtrak railway stations",
    "edition": "USDOT BTS frozen GeoBenchX 2025 snapshot",
    "units": {},
    "collectionId": "blue-generated--[resource id withheld]",
    "itemId": "[resource id withheld]",
    "assetKey": "data"
  },
  {
    "name": "US snowfall, 2024\u201325 frozen season",
    "edition": "2024-09-30 to 2025-05-20",
    "units": {
      "band1": "inches"
    },
    "collectionId": "blue-generated--[resource id withheld]",
    "itemId": "[resource id withheld]",
    "assetKey": "data"
  }
]

Outcome & verification

Final count or unknown-coverage count disagrees with the computed evidence.

Duration
19m 51s
Recorded Blue tool calls
62
Total tokens
3,319,453
Model cost
Not recorded
Application revision
d50497ea9084f29c91b05406688f87035df98d8a
Release
terra-geobenchx-v1

Recorded final answer

Done — the heatmap is on your map, and the selected-station artifact is retained for inspection with original geometry and `benchmark_row_id`. It uses the frozen USDOT BTS GeoBenchX 2025 Amtrak station snapshot and the frozen NOAA/NWS NOHRSC 2024–25 snowfall raster. I kept 202 USA-coded stations whose sampled band-1 snowfall was strictly above 39.37 inches, used sampled `snow_depth` in inches as the weight, and smoothed them on the fixed EPSG:6933 25 km grid with a 150 km Gaussian radius. Main limits: 36 USA-coded records had unknown snowfall samples and were not counted, 16 BC/ON/QC records were excluded outside the requested geography, and the raster values are summed inches per cell, not station counts or per-square-kilometre density. ### Limitations - Outside-USA exclusion follows the source State/province codes in the station snapshot rather than a separate boundary geometry, matching the task convention. - NoData and off-grid snowfall samples remain unknown and do not contribute to the heatmap. - Geography filtering follows the source State and province codes in the supplied station snapshot rather than a separate boundary geometry. - Thirty-six USA-coded station records had unknown snowfall samples and do not contribute; sixteen BC, ON and QC records were excluded outside the requested geography. - Heatmap values are weighted sums of snowfall inches per 25 km grid cell, not station counts and not per-square-kilometre density. - Constant-zero exterior with no edge renormalization can reduce smoothed totals near the fixed grid boundary, although outsideGridCount was 0 for the contributing points. - USA membership follows the source State field codes in the supplied snapshot rather than a separate boundary geometry. - Unknown snowfall samples remain outside the contributing artifact and are counted separately. - USA membership follows the source State field in the supplied snapshot rather than a separate boundary geometry. - NoData and off-grid samples remain null and do not become zero or interpolated values. - Output values are sum of inches per grid cell, not per-square-kilometre density. - Constant-zero exterior can reduce mass near the fixed grid boundary.

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
202
Reported count
202
Computation verified
Yes
Answer fulfilled
No
Full grading and rubric record
{
  "expectedCount": 202,
  "actualCount": 202,
  "expectedMetrics": null,
  "actualMetrics": null,
  "computationCorrect": true,
  "answerFulfilled": false,
  "adjudication": null,
  "qualification": null,
  "reasons": [
    "Final count or unknown-coverage count disagrees with the computed evidence."
  ]
}

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

Can the supplied station snapshot be sampled against the frozen snowfall raster, filtered by sampled snowfall > 39.37 inches, and turned directly into the declared snowfall-weighted fixed-grid heatmap without extra preparation?

assess_trial · completed · assessment: sufficient

The trial confirmed the end-to-end analytical path. Raster-sample wrote a numeric snow_depth field from snowfall band 1 onto all 1,020 original station records, with 52 null samples that must remain unknown. A strict vector filter on snow_depth > 39.37 retained 202 stations and preserved original point geometry plus benchmark_row_id. Point-density accepted snow_depth as the weight field, used all 202 selected points with unknownWeightCount 0, and produced an EPSG:6933 raster with bounds [-18000000,-7325000,18000000,7325000], 25,000 m by 25,000 m cells, radius 150,000 m, sigmaPixels [2,2], kernelTruncateSigma 4, and unit 'sum of inches per grid cell'.

assess_result · completed · assessment: sufficient

I verified the retained contributing-point artifact. It contains 202 eligible USA-coded station records with original point geometry, benchmark_row_id and finite sampled snow_depth values above the strict 39.37-inch threshold. Unknown records remain separate from the contributing artifact: 36 USA-coded records have null snowfall samples, and 16 BC/ON/QC records are outside the requested geography and excluded.

assess_result · failed · requested assessment: sufficient

I verified the final snowfall-weighted station heatmap and its contributing-point artifact. Sources: Amtrak railway stations, USDOT BTS frozen GeoBenchX 2025 snapshot hosted by Blue, retrieved 2026-10-07; US snowfall, NOAA/NWS NOHRSC frozen season 2024-09-30 to 2025-05-20 hosted by Blue, retrieved 2026-10-07. The final run contributed 202 USA-coded station records with sampled snowfall weights totaling 17096.160598754883 inches. The heatmap raster uses the declared fixed EPSG:6933 grid, 25 km by 25 km cells, radius 150000 metres, and unit 'sum of inches per grid cell'. The raster is now on the map.

assess_result · failed · requested assessment: sufficient

I verified the final snowfall-weighted station heatmap and its contributing-point artifact. Sources: Amtrak railway stations, USDOT BTS frozen GeoBenchX 2025 snapshot hosted by Blue, retrieved 2026-10-07; US snowfall, NOAA/NWS NOHRSC frozen season 2024-09-30 to 2025-05-20 hosted by Blue, retrieved 2026-10-07. The final run contributed 202 USA-coded station records with sampled snowfall weights totaling 17096.160598754883 inches. The heatmap raster uses the declared fixed EPSG:6933 grid, 25 km by 25 km cells, radius 150000 metres, and unit 'sum of inches per grid cell'. The raster is on the map.

assess_result · completed · assessment: sufficient

I verified the final snowfall-weighted station heatmap and its contributing-point artifact. Sources: Amtrak railway stations, USDOT BTS frozen GeoBenchX 2025 snapshot hosted by Blue, retrieved 2026-10-07; US snowfall, NOAA/NWS NOHRSC frozen season 2024-09-30 to 2025-05-20 hosted by Blue, retrieved 2026-10-07. The final run contributed 202 USA-coded station records with sampled snowfall weights totaling 17096.160598754883 inches. The heatmap raster uses the declared fixed EPSG:6933 grid, 25 km by 25 km cells, radius 150000 metres, and unit 'sum of inches per grid cell'. The raster is on the map as layer [resource id withheld].

Recorded workflow

  1. 01

    Snowfall-weighted station heatmap

    Recorded output · succeeded

  2. 02

    Selected snowy USA stations

    Recorded output · succeeded

  3. 03

    density

    Recorded point-density · succeeded

  4. 04

    sampled

    Recorded raster-sample · succeeded

  5. 05

    selected

    Recorded vector-filter · succeeded

  6. 06

    blue-generated--[resource id withheld]

    Recorded source · succeeded

  7. 07

    blue-generated--[resource id withheld]

    Recorded source · succeeded

  8. 08

    density

    Recorded point-density · succeeded

  9. 09

    sampled

    Recorded raster-sample · succeeded

  10. 10

    selected

    Recorded vector-filter · succeeded

  11. 11

    blue-generated--[resource id withheld]

    Recorded source · succeeded

  12. 12

    blue-generated--[resource id withheld]

    Recorded source · succeeded

  13. 13

    sampled

    Recorded output · succeeded

  14. 14

    selected

    Recorded output · succeeded

  15. 15

    density

    Recorded output · succeeded

  16. 16

    density

    Recorded output · succeeded

  17. 17

    sampled

    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 station and snowfall datasets first, then I’ll test the exact sampling and weighting rule on a small private slice before I save the full USA method.

  2. get_analysis

    Recorded tool call · completed

  3. get_collection

    Recorded tool call · completed

  4. get_collection

    Recorded tool call · completed

  5. Progress update

    I found the two immutable inputs. Next I’m checking the station fields and the available processors so I can match the benchmark rules exactly: sample the original snowfall raster at each point, keep only USA stations above 39.37 inches, carry sampled inches forward as the weight, and only then build the heatmap on the fixed metric grid.

  6. get_item

    Recorded tool call · completed

  7. get_tool_help

    Recorded tool call · completed

  8. get_item

    Recorded tool call · completed

  9. list_processors

    Recorded tool call · completed

  10. describe_processors

    Recorded tool call · completed

  11. get_collection

    Recorded tool call · completed

  12. get_collection

    Recorded tool call · completed

  13. Progress update

    I’ve confirmed the source editions and the available core processors. The remaining uncertainty is practical: what field name the raster sampler writes, and whether the snowy-station subset comes through cleanly enough to drive the weighted heatmap without extra preparation. I’m running a small private slice to answer that before I save the full USA workflow.

  14. describe_processors

    Recorded tool call · completed

  15. get_tool_help

    Recorded tool call · completed

  16. update_analysis_brief

    Recorded tool call · completed

  17. run_trial

    Recorded tool call · completed

  18. Progress update

    The trial succeeded, so the core method works: the sampler writes `snow_depth`, the strict snow filter keeps a clean subset, and the weighted heatmap lands on the fixed EPSG:6933 grid with the right units and Gaussian settings. One important gap remains before the full run: this snapshot includes some non‑US stations, so I still need an actual USA boundary to exclude valid points outside the requested geography and to separate excluded records from unknown ones. Then I can save and run the full workflow.

  19. get_trial_report

    Recorded tool call · completed

  20. assess_trial

    Recorded tool call · completed

  21. search_catalog

    Recorded tool call · completed

  22. search_catalog

    Recorded tool call · completed

  23. inspect_artifact

    Recorded tool call · completed

  24. inspect_artifact

    Recorded tool call · completed

  25. Progress update

    I found a practical ambiguity in the benchmark wording: the supplied station snapshot appears to include some non‑US records, and the task also says not to infer a separate geographic boundary. I’m checking whether the original records themselves carry enough geography to exclude those stations exactly, so I can avoid bringing in an outside boundary if the snapshot already supports the filter.

  26. inspect_artifact

    Recorded tool call · completed

  27. inspect_artifact

    Recorded tool call · completed

  28. inspect_artifact

    Recorded tool call · completed

  29. inspect_artifact

    Recorded tool call · completed

  30. Progress update

    I’m resolving the last selection detail before the full run: whether the supplied station records themselves carry a reliable USA indicator, so I can follow the benchmark instruction without inventing a separate boundary. After that I can save the production workflow and run it.

  31. inspect_artifact

    Recorded tool call · completed

  32. Progress update

    I’ve confirmed the USA filter can come from the original records themselves: `State` uses US abbreviations for US records and province codes like BC, ON, and QC for non‑US records in this snapshot. I’m pulling the exact counts now so the final result separates excluded outside-USA records from truly unknown eligibility.

  33. inspect_artifact

    Recorded tool call · completed

  34. inspect_artifact

    Recorded tool call · completed

  35. inspect_artifact

    Recorded tool call · completed

  36. Progress update

    The method is tested. I’m switching from trial work to the saved production run now: same sampling and smoothing path, with the record-based USA filter added so outside stations are excluded instead of being treated as unknown.

  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. inspect_artifact

    Recorded tool call · completed

  41. inspect_artifact

    Recorded tool call · completed

  42. inspect_artifact

    Recorded tool call · completed

  43. get_tool_help

    Recorded tool call · completed

  44. get_tool_help

    Recorded tool call · completed

  45. get_tool_help

    Recorded tool call · completed

  46. get_tool_help

    Recorded tool call · completed

  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. get_tool_help

    Recorded tool call · completed

  51. get_tool_help

    Recorded tool call · completed

  52. get_tool_help

    Recorded tool call · completed

  53. Progress update

    I’ve finished the method development. The last facts are now clear: the sampler writes `snow_depth`; 202 stations meet the strict snow rule; all of those contributors are already USA-coded in the source records; and 36 USA-coded records have unknown snow samples while 16 Canada-coded records are outside the requested geography and should be excluded, not counted as unknown. Now I’m saving the full workflow and running it.

  54. update_analysis_brief

    Recorded tool call · completed

  55. propose_workflow

    Recorded tool call · completed

  56. Progress update

    The workflow saved, but the contract needs one small repair before execution: I have to bind the snow-threshold requirement to the selected-point input, not to the literal threshold value. That is a wiring fix, not a method change.

  57. revise_workflow

    Recorded tool call · completed

  58. execute_workflow

    Recorded tool call · completed

  59. inspect_workflow_results

    Recorded tool call · completed

  60. Progress update

    I’m doing the last verification on the final artifacts: one check on the selected stations, one on the heatmap raster, and one on the sampled source points so the reported unknown count reflects the final run rather than the earlier trial.

  61. inspect_artifact

    Recorded tool call · completed

  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. inspect_artifact

    Recorded tool call · completed

  69. Progress update

    The run itself is done and the heatmap is already on the map. I’m just collecting the final bounded inspection receipts needed to attach the result cleanly: the raster preview, a small row sample from the contributing stations, and the final unknown/outside counts from the sampled source points.

  70. assess_result

    Recorded tool call · completed

  71. assess_result

    Recorded tool call · failed

  72. Progress update

    Blue rejected the wording because the final assessment has to use the exact stored acceptance-condition text. I’m correcting only that assessment formatting now; the inspected artifacts and counts are unchanged.

  73. assess_result

    Recorded tool call · failed

  74. get_analysis

    Recorded tool call · completed

  75. Progress update

    I have the exact stored condition text now. I’m retrying the final assessment with only those five required heatmap conditions, then I’ll return the short confirmation.

  76. assess_result

    Recorded tool call · completed

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