Bibliographic record
Abstract
The Northern Mariner / Le marin du nord Then at 9:36 pm (13 minutes after the second signal), the fateful and most criticized "Most Immediate" signal for the convoy to scatter! "Scattering" and "dispersing" were not synonymous!With that signal, most escorts turned about and abandoned the neardefenseless freighters.The latter headed in all directions -those that headed more or less directly to Russia were picked off by U-boats and aircraft, while those that headed north into the icefield fared better.The armed trawler Ayrshire and three ships (Troubadour, Ironclad, and Silver Sword) painted themselves white and became ghosts (hence the title of the book), practically invisible in the icefield.The story line of the book, as seen through the eyes of their sailors, tells of their exploits in the ice and along the coast of Novaya Zemlya, a dash to Archangel with a few other ships which had found their way to that island, and then their experiences in the Russian port.I recommend this book because, not only does it tell the full story of PQ-17, but also provides the human element of wartime experiences and of life on board ships and in Russia.The "Notes on Sources" is not just "end notes" but a much fuller rendering of information and obiter dicta.The book concludes with a chapter called "The Reckoning."Need I say more?
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.055 | 0.019 |
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".