The Dazzling Zoologist John Graham Kerr and the Early Development of Ship Camouflage
Bibliographic record
Abstract
un scientifique et naturaliste bas l'universit de Glasgow a offert l'Amiraut un systme semblable tout au dbut de la premire guerre mondiale. Le systme de Kerr a t bas sur ses observations de la nature et de ses connaissances des exprimentations dans le camouflage par Abbott H. Thayer et George de Forest Brush aux Etats-Unis. En dpit de l'acceptation initiale des ides de Kerr, l'Amiraut ne les a pas menes leur conclusion logique. Wilkinson, qui avait vu certaines des ides de Kerr mises en pratique pendant la campagne des Dardanelles, a rfut plus tard toute suggestion d'influence de Kerr. Cet article analyse la contribution de Kerr et conclut que son influence tait en fait plus importante que n'est crdit dans la littrature sur le camouflage des navires.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".