Bibliographic record
Abstract
Characteristics .—Black; a brown or yellowish patch on each side of the nose. Description .—Oval erect ears, rounded at the tips; the hair projects slightly beyond the claws, which are short and blunt. Long, shining, straight, and rather soft fur. Colour .—Generally black, though in some instances a brownish tinge is observable in the fur; the sides of the nose are of a fawn colour. Very often found with a dash of white under the throat, and rarely, though sometimes they have been found, with a white star in the forehead. Found from Mexico to Labrador, and from the Atlantic to the Pacific. THE black bear is found throughout the American continent, except in a very small district to the north-east, where civilisation has dislodged him from the country. They abound in the extreme North Canada and the snow-bound regions of the Hudson's Bay territory; and in the Southern States, in Mississippi, in Louisiana, in Arkansas, in Texas, and Florida, the bear-hunt still ranks amongst the established field sports, and the hunters have no reason to complain of scarcity of game. A hundred years ago the peculiar and special haunt of the black bear was in the dense cane-brakes that fringed the banks of the Ohio and Mississippi rivers. In these districts the settlers formerly suffered great losses from the depredations of the ‘ varmint ;’ cornpatches, gardens, and even hog-pens, being robbed by these unscrupulous freebooters.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.067 | 0.020 |
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".