Bibliographic record
Abstract
with a number of excellent photographs of the young ducks and snapshots of flocks of old birds on the wing.This is Mr. Job's second experiment in securing young wild ducks, the previous summer having been spent at Lake Manitoba when about 100 young, of the later breeding species, were obtained, although he was then too late for the Canvasbacks.The further experiments of the author in rearing these birds will be watched with interest and all bird-lovers and sportsmen will join in his hope "that they may duly multiply and help to replenish the earth in our eastern districts so woefully lacking in these splendid wild fowl."--W.S. Mearns on Additional New Birds from Africa J--Dr.Mearns' latest contribution to African ornithology consists of the description of ten new subspecies contained in the several collections recently added to the U.S. National Museum collection.These are Pogonocichla cucullata helleri, Mr. Mbololo; Cossypha natalensis garguensis, Mr. Gargues; C. natalensis intensa, Taveta; Bradypterus bab,eculus fraterculus, Escarpment; Sylvietta leucophrys keniensis, Mr. Kenia; S. brachyura tavetensis, Taveta; Zosterops senegalensis fricki, Thika River; and Z. virens garguensis, Mr. Gargucs, all in British East Africa; while from Abyssinia are described Sylvietta whytii abayensis, Gardulla; and Melamparus afer fricki, Dire Daoua.--W
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.055 | 0.008 |
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".