Applications of Iceberg Profiling Data to Improve Iceberg Management Success
Bibliographic record
Abstract
Abstract Hibernia Management and Development Company Ltd. (HMDC) sponsored a R&D initiative in 2012 with the objective of obtaining high quality three dimensional iceberg profiles off the east coast of Newfoundland and Labrador. The three dimensional iceberg profiles collected during that program have been used in this work to illustrate the potential benefits to iceberg management which could be realized if towing vessels were outfitted with the equipment required to obtain three dimensional iceberg shapes quickly in the field. Tools have been developed under the further financial support of HMDC to assess the stability of the iceberg in order to identify the preferential towing directions to reduce the likelihood of rolling the iceberg during a tow. A tool has also been developed to allow the user to assess the local shape of the iceberg relative to the towing net to help avoid unfavorable iceberg shapes and slopes. The iceberg shapes have also been used to assess the current iceberg towing net design with recommendations for potential improvements to reduce net slippage during a tow.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 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".