Applying Agreed-Upon Procedures: Airport and Airway Trust Fund Excise Taxes
Bibliographic record
Abstract
Correspondence issued by the Government Accountability Office with an abstract that begins "We assisted the Department of Transportation in ascertaining whether the net excise tax revenue distributed to the Airport and Airway Trust Fund (AATF) for the fiscal year ended September 30, 2004, is supported by the underlying records. In performing the agreed-upon procedures, we conducted our work in accordance with U.S. generally accepted government auditing standards, which incorporate financial audit and attestation standards established by the American Institute of Certified Public Accountants. The procedures we agreed to perform were (1) transactions that represent the underlying basis of amounts distributed to the AATF, (2) the Internal Revenue Service's (IRS) quarterly AATF certifications, (3) the Department of the Treasury's Financial Management Service adjustments to the AATF for fiscal year 2005, (4) IRS's precertification of receipts for the second and third quarters of fiscal year 2005, (5) certain procedures of the Department of the Treasury's Office of Tax Analysis' (OTA) estimation procedures affecting excise tax distributions to the AATF for the fourth quarter of fiscal year 2005, and other procedures including (6) the net amount of fiscal year 2005 excise taxes distributed to the AATF, (7) transactions that represent total IRS tax revenue receipts and refunds, and (8) key reconciliations of IRS records to Treasury records."
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.072 | 0.223 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.064 | 0.039 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".