St. Lawrence Seaway: Estimates for the Asset Renewal Program Will Change, and Implementing Best Practices May Improve the Estimates' Reliability
Bibliographic record
Abstract
Correspondence issued by the Government Accountability Office with an abstract that begins "The St. Lawrence Seaway is a 50-year-old binational transportation asset jointly operated by the United States and Canada that is used to move cargo between North America and international markets. In 2009, the U.S. Saint Lawrence Seaway Development Corporation (SLSDC), which is responsible for operating and maintaining the two locks and navigation channels in the U.S. portion of the Seaway, initiated a 10-year Asset Renewal Program (ARP) to address long-term needs of the locks, navigation channels, and related facilities and equipment. In 2009, Congress instructed GAO to examine the ARP. Accordingly, GAO examined (1) how the cost estimates have changed from February 2009 to February 2010, (2) the extent to which the ARP covers all asset renewal needs, and (3) the steps U.S. and Canadian authorities have taken to coordinate their asset renewal programs. To conduct this work, GAO reviewed agency program documents, interviewed SLSDC officials, and analyzed ARP estimates and fiscal year 2009 contract data."
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 | 0.009 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.010 |
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".