Bibliographic record
Abstract
Many years ago I ordered from the Italian Ministry of Marine two of their official histories, I Cacciatorpediniere Italiana on the history of their torpedoboats and destroyers, and Gli Incrociatori Italiani on their cruisers.Both were superlatively produced, large and useful references, although I was appalled at the cost-about 4,000 lire.I was much relieved to discover that it amounted to about $8.00 Canadian!This volume, published by the Naval Institute Press and printed in China, still retains the quality of the earlier series, the original Italian edition being published in 2010.Notably, the translation by Raphael Riccio is also skilful, literate and, as far as I noted, flawless in idiomatic English.It is the quality one might expect from a book on Italian art and literature.With two fold-out charts illustrating changes in the ships' camouflage over time, external views of two of the ships, hull lines, longitudinal sections, and three-dimensional views of two of the fighter aircraft carried, this is quite a remarkable publication.It should assuredly be taken as a guide for others to copy, whatever the national ships.Apart from its impressive appearance, the story of these three unique ships is complete and logically told.The authors open with a section on developing
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.415 | 0.383 |
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".