Sea Fog Research in the United Kingdom and United States: A Historical Essay Including Outlook
Bibliographic record
Abstract
A historical review of research on sea fog is presented. The period of interest is essentially the twentieth century, beginning with the celebrated work of G. I. Taylor in the aftermath of the Titanic tragedy. It has been argued that relative maxima in fog frequency over the North Atlantic (including the British Isles and the Grand Banks of Newfoundland) and the North Pacific (including the U.S. West Coast) has led to major contributions by scientists in England and the United States. The early work (pre-World War II) tended to be phenomenological—that is, conceptual with broad inference from statistical summaries. Yet, this early work laid the foundation for the numerical modeling that came with the advent of computers in the postwar period. The subtleties associated with sea fog formation and maintenance are explored by analyzing some of the results from the numerical simulations. The essay ends with a speculative view on our prospects for a more complete understanding of sea fog in light of the earlier contributions.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".