Bibliographic record
Abstract
History The first observations of icebergs were probably made by Inuit hunters in the Arctic and then by early mariners, including Irish monks and Vikings. Martin Frobisher’s expeditions to Baffin Island in the 1570s to 1580s certainly witnessed them and whalers and sealers in Baffin Bay and the Greenland Sea frequently sheltered in their lee from storms and sea ice. Documentation of icebergs in the northwest Atlantic began in 1914 by the International Ice Patrol after the loss of the RMS Titanic , and over 1,500 lives, due to a collision with an iceberg in April 1912. The First International Conference for the Safety of Life at Sea established the Ice Patrol, operated by the US Coast Guard, in 1913. It conducts surveys of the icebergs that drift south of 48° N off Newfoundland. Initially this was from cutters, and then airborne reconnaissance flights started in 1946 using first visual observations; airborne radar studies began in 1957 and in 1983 Side-Looking Airborne Radar (SLAR) was deployed. After 1991 (1995) radar remote sensing made use of data from ERS-1 (ERS-2), and RADARSAT’s synthetic aperture radar (SAR), beginning in 1995. A major concern is the hazard to drilling platforms off the coast of Newfoundland.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 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".