thesisPrototype

Government data

FY2026 HIDTA AL 95.001 obligations

For FY2026, what will the USAspending API v2 advanced search spending_over_time endpoint return on the first registered-query snapshot for results[time_period.fiscal_year=2026].aggregated_amount, scaled to usd_millions, for prime financial-assistance award transactions filtered to Assistance Listing 95.001, grouped by action-date federal fiscal year, not seasonally adjusted?

Forecast

$271.658M
$257.223M–$286.093M
80% prediction interval
gpt-5.5Run record ↗

Cumulative probability

Chance that the outcome is at or below each value.

0%25%50%75%100%$235.571M$271.658M$307.745MForecast value

Shaded band: 80% interval ($257.223M–$286.093M). Dashed line: point estimate ($271.658M).

Derived from the point estimate and 80% interval; the agent did not report a full distribution.

Analysis

§FY2026 HIDTA AL 95.001 registered-query forecast

Resolution framing: the target is the USAspending API v2 spending_over_time registered query for Assistance Listing 95.001 prime financial-assistance award transactions, fiscal-year grouped, first archived registered-query snapshot for FY2026. The target registration supplies expectedReleaseWindow 2026-10-15 to 2026-10-22, so I use the lab-committed outer bound 2026-10-22 rather than inferring a release day from cadence.

▸ Reported tool use: repo_and_specs.checkmodel report
Parsed records/targets/2026-08-11-eb895fc1e680eab66d27b1046b6df148fa4c00829fc42935f4c36fb1c8a4a42a.json and fetched https://app.thesisinstitute.org/specs.json
↳ Target registration parsed with catalogSlug us-ondcp-hidta-al95001-obligations-fy2026, targetContentHash eb895fc1e680eab66d27b1046b6df148fa4c00829fc42935f4c36fb1c8a4a42a, expectedReleaseWindow.end 2026-10-22, sourceUrl https://api.usaspending.gov/api/v2/search/spending_over_time/. Fetched specs.json size was 11289 bytes; rg found 0 occurrences of us-ondcp-hidta-al95001-obligations-fy2026.
▸ Reported tool use: usaspending.spending_over_timemodel report
POST group=fiscal_year, spending_level=transactions, program_numbers=[95.001], award_type_codes=[02..11], FY2019-FY2021 time_periods
↳ USAspending echoed FY2019 aggregated_amount 284145146.31 dollars = 284.14514631 usd_millions; FY2020 aggregated_amount 270271443.68 dollars = 270.27144368 usd_millions; FY2021 aggregated_amount 268605305.17 dollars = 268.60530517 usd_millions.
▸ Reported tool use: usaspending.spending_over_timemodel report
POST same registered query for FY2022-FY2024 time_periods
↳ USAspending echoed FY2022 aggregated_amount 252760500.27 dollars = 252.76050027 usd_millions; FY2023 aggregated_amount 266415446.91 dollars = 266.41544691 usd_millions; FY2024 aggregated_amount 273959946.11 dollars = 273.95994611 usd_millions.
▸ Reported tool use: usaspending.spending_over_timemodel report
POST same registered query for FY2025 completed period and FY2026 target period as currently visible
↳ USAspending echoed FY2025 aggregated_amount 271657675.6 dollars = 271.6576756 usd_millions. The same FY2026 target-period query, fetched during this run before the registered snapshot window, echoed aggregated_amount 262984.51 dollars = 0.26298451 usd_millions, which is not comparable to completed fiscal-year snapshots.
▸ Reported tool use: brier.timeseriesmodel report
PYTHONPATH=. python3 scripts/run_time_series_models.py --target-id usaspending.ondcp.hidta_al95001_obligations.fy2026.registered_query_snapshot --target-period FY2026 --models persistence --round-increment 0.000001 with FY2019-FY2025 fetched history
↳ thesis_model_candidate_v1 persistence.last_print generatedAt 2026-08-12T20:55:30Z: pointEstimate 271.657676, p10 256.798422, p50 271.657676, p90 282.257399, interval80 lower 256.798422 upper 282.257399, interval90 lower 256.305646 upper 283.78501, intervalMethod residual_quantile, calibrationN 6, walk_forward_1_step meanAbsoluteError 9.147727064999989.

Base rate / reference class: the last 7 completed fiscal-year registered-query values were 284.14514631, 270.27144368, 268.60530517, 252.76050027, 266.41544691, 273.95994611, and 271.6576756 usd_millions. Their mean was 269.687923, median 270.271444, range 252.760500-284.145146, and the strongest simple benchmark is last-print persistence at FY2025 = 271.6576756 usd_millions.

Prior/update/interval: prior = persistence.last_print candidate from FY2019-FY2025 completed registered-query history, point 271.657676. Adjustment components: 0.000000 for current FY2026 live-query value because 0.26298451 usd_millions is an in-year continuous USAspending value before the registered snapshot window and not a comparable final fiscal-year snapshot; no other direct current signal was fetched. For interval sizing on this annual flow series, sample sigma = 9.397701 from the 7 completed fetched values; 1.28*sigma = 12.029057. I widen the half-width by 1.20x to 14.434868 because USAspending registered_query_snapshot outcomes can move with late-posted/revised transactions between the live query and the October capture window; this is deliberately wider than the residual-quantile candidate's p10-p90 interval upper bound of 282.257399. Final 80% interval = 271.657676 +/- 14.434868 = [257.222807, 286.092545]. This interval would contain 6 of the 7 completed FY2019-FY2025 registered-query values.

Counter-consideration: upside risk outside the interval would be a late FY2026 bulk HIDTA grant obligation or cleanup transaction that pushes the AL 95.001 fiscal-year aggregate above about 286.1 usd_millions. Downside risk outside the interval would land below the interval if FY2026 awards remain unusually delayed, reclassified, or deobligated so that the October registered snapshot stays below about 257.2 usd_millions.

Review disposition: accepted the resolver wording cleanup by quoting Assistance Listing "95.001" and mirroring the registered transform field names programNumbers, awardTypeCodes, group, and spendingLevel. Accepted the optional clarification that the selected interval is deliberately wider than the model candidate's residual-quantile p10-p90 interval; retained the FY2026 live-query value only as non-comparable pre-window evidence.

Key drivers

  • last completed fiscal-year persistence
  • stable FY2019-FY2025 AL 95.001 range
  • continuous USAspending revision/snapshot risk
  • FY2026 live query not yet comparable to final snapshot

Tool evidence

This run has no captured tool responses. “Reported tool use” in the analysis is the model’s account, not an archived tool response.

Sources and resolution

Official source
USAspending API v2 advanced search registered-query snapshot
Resolution date
October 22, 2026· outcome not recorded
Resolution rule
Resolve from the first archived registered-query snapshot captured in the Thesis expected release window 2026-10-15 through 2026-10-22, with resolutionDate equal to the lab-committed outer bound 2026-10-22. POST to the USAspending API v2 /api/v2/search/spending_over_time/ endpoint using the registered transform fields: group fiscal_year, spendingLevel transactions, programNumbers ["95.001"], awardTypeCodes ["02","03","04","05","06","07","08","09","10","11"], and requestMethod POST, with the FY2026 fiscal-year time period 2025-10-01 through 2026-09-30. Read the unique result where time_period.fiscal_year is 2026, take aggregated_amount in dollars, multiply by 0.000001, and report in usd_millions. This is a registered_query_snapshot / first snapshot rule; later USAspending revisions are irrelevant.
Run details

The analysis is the model’s written report. Tool-use descriptions in that report are model claims; the activity artifacts contain the execution record.

thesis.analyst · gpt-5.5 · full · v2.5.9

pre-submit review · completed

Draft is publishable with only minor resolver wording cleanup needed to remove avoidable ambiguity around the exact registered query body.

  • warning resolver: The resolution rule paraphrases the registered query but writes program_numbers as [95.001], which can read as a numeric value rather than the exact string in sourceBinding.transform.programNumbers.
  • info optional_suggestion: Mention that the time-series residual-quantile candidate gave a narrower upper p90 than the chosen widened interval, so the manual widening is deliberate rather than a transcription mismatch.
  • info optional_suggestion: Keep the FY2026 live-query value framed only as non-comparable pre-window evidence, as the draft already does.

disposition accepted: Review disposition: accepted the resolver wording cleanup by quoting Assistance Listing "95.001" and mirroring the registered transform field names programNumbers, awardTypeCodes, group, and spendingLevel. Accepted the optional clarification that the selected interval is deliberately wider than the model candidate's residual-quantile p10-p90 interval; retained the FY2026 live-query value only as non-comparable pre-window evidence.

disposition not applicable: Review disposition: accepted the resolver wording cleanup by quoting Assistance Listing "95.001" and mirroring the registered transform field names programNumbers, awardTypeCodes, group, and spendingLevel. Accepted the optional clarification that the selected interval is deliberately wider than the model candidate's residual-quantile p10-p90 interval; retained the FY2026 live-query value only as non-comparable pre-window evidence.

disposition not applicable: Review disposition: accepted the resolver wording cleanup by quoting Assistance Listing "95.001" and mirroring the registered transform field names programNumbers, awardTypeCodes, group, and spendingLevel. Accepted the optional clarification that the selected interval is deliberately wider than the model candidate's residual-quantile p10-p90 interval; retained the FY2026 live-query value only as non-comparable pre-window evidence.

Activity artifacts

Complete original trace

§FY2026 HIDTA AL 95.001 registered-query forecast

Resolution framing: the target is the USAspending API v2 spending_over_time registered query for Assistance Listing 95.001 prime financial-assistance award transactions, fiscal-year grouped, first archived registered-query snapshot for FY2026. The target registration supplies expectedReleaseWindow 2026-10-15 to 2026-10-22, so I use the lab-committed outer bound 2026-10-22 rather than inferring a release day from cadence.

▸ Reported tool use: repo_and_specs.checkmodel report
Parsed records/targets/2026-08-11-eb895fc1e680eab66d27b1046b6df148fa4c00829fc42935f4c36fb1c8a4a42a.json and fetched https://app.thesisinstitute.org/specs.json
↳ Target registration parsed with catalogSlug us-ondcp-hidta-al95001-obligations-fy2026, targetContentHash eb895fc1e680eab66d27b1046b6df148fa4c00829fc42935f4c36fb1c8a4a42a, expectedReleaseWindow.end 2026-10-22, sourceUrl https://api.usaspending.gov/api/v2/search/spending_over_time/. Fetched specs.json size was 11289 bytes; rg found 0 occurrences of us-ondcp-hidta-al95001-obligations-fy2026.
▸ Reported tool use: usaspending.spending_over_timemodel report
POST group=fiscal_year, spending_level=transactions, program_numbers=[95.001], award_type_codes=[02..11], FY2019-FY2021 time_periods
↳ USAspending echoed FY2019 aggregated_amount 284145146.31 dollars = 284.14514631 usd_millions; FY2020 aggregated_amount 270271443.68 dollars = 270.27144368 usd_millions; FY2021 aggregated_amount 268605305.17 dollars = 268.60530517 usd_millions.
▸ Reported tool use: usaspending.spending_over_timemodel report
POST same registered query for FY2022-FY2024 time_periods
↳ USAspending echoed FY2022 aggregated_amount 252760500.27 dollars = 252.76050027 usd_millions; FY2023 aggregated_amount 266415446.91 dollars = 266.41544691 usd_millions; FY2024 aggregated_amount 273959946.11 dollars = 273.95994611 usd_millions.
▸ Reported tool use: usaspending.spending_over_timemodel report
POST same registered query for FY2025 completed period and FY2026 target period as currently visible
↳ USAspending echoed FY2025 aggregated_amount 271657675.6 dollars = 271.6576756 usd_millions. The same FY2026 target-period query, fetched during this run before the registered snapshot window, echoed aggregated_amount 262984.51 dollars = 0.26298451 usd_millions, which is not comparable to completed fiscal-year snapshots.
▸ Reported tool use: brier.timeseriesmodel report
PYTHONPATH=. python3 scripts/run_time_series_models.py --target-id usaspending.ondcp.hidta_al95001_obligations.fy2026.registered_query_snapshot --target-period FY2026 --models persistence --round-increment 0.000001 with FY2019-FY2025 fetched history
↳ thesis_model_candidate_v1 persistence.last_print generatedAt 2026-08-12T20:55:30Z: pointEstimate 271.657676, p10 256.798422, p50 271.657676, p90 282.257399, interval80 lower 256.798422 upper 282.257399, interval90 lower 256.305646 upper 283.78501, intervalMethod residual_quantile, calibrationN 6, walk_forward_1_step meanAbsoluteError 9.147727064999989.

Base rate / reference class: the last 7 completed fiscal-year registered-query values were 284.14514631, 270.27144368, 268.60530517, 252.76050027, 266.41544691, 273.95994611, and 271.6576756 usd_millions. Their mean was 269.687923, median 270.271444, range 252.760500-284.145146, and the strongest simple benchmark is last-print persistence at FY2025 = 271.6576756 usd_millions.

Prior/update/interval: prior = persistence.last_print candidate from FY2019-FY2025 completed registered-query history, point 271.657676. Adjustment components: 0.000000 for current FY2026 live-query value because 0.26298451 usd_millions is an in-year continuous USAspending value before the registered snapshot window and not a comparable final fiscal-year snapshot; no other direct current signal was fetched. For interval sizing on this annual flow series, sample sigma = 9.397701 from the 7 completed fetched values; 1.28*sigma = 12.029057. I widen the half-width by 1.20x to 14.434868 because USAspending registered_query_snapshot outcomes can move with late-posted/revised transactions between the live query and the October capture window; this is deliberately wider than the residual-quantile candidate's p10-p90 interval upper bound of 282.257399. Final 80% interval = 271.657676 +/- 14.434868 = [257.222807, 286.092545]. This interval would contain 6 of the 7 completed FY2019-FY2025 registered-query values.

Counter-consideration: upside risk outside the interval would be a late FY2026 bulk HIDTA grant obligation or cleanup transaction that pushes the AL 95.001 fiscal-year aggregate above about 286.1 usd_millions. Downside risk outside the interval would land below the interval if FY2026 awards remain unusually delayed, reclassified, or deobligated so that the October registered snapshot stays below about 257.2 usd_millions.

Review disposition: accepted the resolver wording cleanup by quoting Assistance Listing "95.001" and mirroring the registered transform field names programNumbers, awardTypeCodes, group, and spendingLevel. Accepted the optional clarification that the selected interval is deliberately wider than the model candidate's residual-quantile p10-p90 interval; retained the FY2026 live-query value only as non-comparable pre-window evidence.

calibrated forecast · 80% CI
$271.658M[$257.223M · $286.093M]
Target metadata

Data point: usaspending.ondcp.hidta_al95001_obligations.fy2026.registered_query_snapshot

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