Analysis and Results of 30 Years of Iceberg Management
Bibliographic record
Abstract
Iceberg management operations have been conducted off eastern Canada for the past 30 years. Various analyses on the success of those operations had been conducted and the results included in reports that were proprietary documents. A small study (Bishop, 1989) analyzed a few years of data and assessed the success of iceberg towing to be 85% while other anecdotal information suggested the success was more like 95%. Provincial Aerospace was contracted to assemble all available iceberg management data into a structured database, with the final outcome to be a publicly available database, capable of providing information to assist in defining ice risk. The PERD Comprehensive Iceberg Management Database contains detailed information on over 1,500 iceberg management operations. These data have helped define bench marks against which future ice management operations can be compared and has directly contributed to a reassessment of the risk of iceberg collision with offshore structures. This paper provides an overview of the database and discusses the results of a subsequent detailed analysis.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".