A 4‐Month Lead Predictor of Open‐Water Onset in Bering Strait
Bibliographic record
Abstract
Abstract This study reveals that the yearday of open‐water onset (topen) in Bering Strait can be predicted with a lead time of about 4 months using a regression equation topen = 37.45CCN + 125.2 (in Julian days), with an averaged absolute error of 5 days and the maximum error of 12 days, where CCN is the ice concentration averaged from 16th January to 15th February near Cape Navarin. This “predictor” is revealed through analyzing the solution of a regional ocean and sea‐ice model. A key factor contribution to the prediction is that the prior winter ice concentration is controlled by the sea surface temperature, and persists into the start of the melting phase near the marginal ice zone in the Cape Navarin area. As ice melts near Cape Navarin, successive melting due to solar heat absorption and lateral heat transport occurs rapidly downstream along Anadyr Current.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".