Bibliographic record
Abstract
F ive years after the discovery of America by Columbus, the English, baffled in their attempts to reach Kathay by the N.E., turned their attention in another direction, and on the morning of the 24th of June, 1497, Newfoundland was discovered by John Cabot. Thus began those series of memorable voyages which have been continued, unto our day, with but short interruption, until the northern seaboard of the American continent has been perfectly discovered. The annals of these Arctic voyages have been read and re-read, published and re-published, evincing the deep interest which generation after generation has taken in these touching records of skill and daring, perseverance and long-suffering; and well may we turn to them with pride and pleasure, exhibiting as they do such proof of that spirit of maritime enterprise which always has been Great Britain's boast and glory. In the year 1500 the discovery of the Cabots was followed up by Gaspar de Cortereal, in two ships from Lisbon, and attention was attracted to the value of the fisheries on the coast of Newfoundland, and in 1504 small vessels from Biscay, Bretagne, and Normandy resorted thither for this purpose. In 1506 Jean Denys drew a map of the Gulf of St. Lawrence; and in 1517 no less than fifty Spanish, French, and Portuguese ships were employed in this fishery.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.539 | 0.343 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".