Overview of the 2012 Iceberg Profiling Program
Bibliographic record
Abstract
Abstract In June of 2012, a 25-day field program was carried out off the east coast of Newfoundland and Labrador with the objective of obtaining high quality 3D profiles of both grounded and freely floating icebergs. The motivation for collecting the data was to provide valuable information relating to the design of offshore platforms in iceberg-prone environments. Specifically, the data was originally acquired to provide insight regarding contact area growth as a function of penetration during a simulated impact with an offshore structure, and to assist in assessing the risk of topsides impact. The above water portion (sail) of the icebergs were profiled using photogrammetry while the below water portion of the icebergs (keel) were profiled using a multibeam system mounted on a remotely operated vehicle (ROV). The drift and rotation of the iceberg during the profiling process was derived using the above water photogrammetry, and was used to correct the below water multibeam data to account for the motion of freely floating icebergs. The drift and rotation was also used to merge the above and below water portions of the iceberg. An overview of the program and resulting data set is presented in this paper. Ultimately, twenty nine three dimensional iceberg profiles were obtained as a result of this work, providing significant improvements in the iceberg shape data available for input in the design of offshore platforms in regions where icebergs present a risk to these structures.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".