Bibliographic record
Abstract
This chapter focuses on John Cabot's discovery of Newfoundland in 1497, a new land that he claimed for England. Although he probably never set foot on the mainland of North America, Cabot found Newfoundland after he went on a mission to find a route to Asia. He then returned to England and reported success to his king, Henry VII, and investors, hoping to obtain funding for a second voyage designed for trade with the people of Asia. The entire second voyage is unknown, except that Cabot departed from Bristol in 1498 and was never seen again. For about twenty-five years after Cabot's voyage of 1497, only cod fishermen sailed to the Newfoundland area, creating a lull in the mapping of North America. Gaspar Corte Real made two voyages into the North Atlantic— to Greenland and Newfoundland—with the authority of the king of Portugal in 1500 and 1501. In 1502, Alberto Cantino made a world map for the Duke of Ferrara based on information from Gaspar's voyages.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 0.005 |
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".