Bibliographic record
Abstract
Hawk Owl in Vernaont.--Mr.Arthur H. Hardisty of Shelburne, Vt., writes me that he shot a Hawk Owl (Surnia ulula caparoch) on November 19, 1926."It was apparently hunting along the roadside when killed and proved to be a male in perfect plumage.It contained a meadow mouse (Microtus)--LEwIs O. SHELLEY, East Westmoreland, N.H.The Carolina Paroquet in Western New ¾ork.--Intabulating recently, some data from notes made many years ago while residing in Buffalo, N.Y., I came across the subjoined item, which in some way had escaped my attention and remained unrecorded until now.While it is of historic value only, it will help round out the rather fragmentary knowledge of this little "parrot.""Mr.David F. Day informed me to-night (Dec.20th, 1889) that he once saw thirteen Carolina Paroquets light on the old City Buildings, Cor. of Franklin and Eagle Streets, and that he knew of a lot being captured at West Seneca (N.Y.) many years ago."Mr. David F. Day was a practicing attorney in Buffalo; his avocation was botany and his knowledge of the flora of western New York was most profound, so much so that Gray drew heavily on it in preparing his 'Manual of Botany.'Mr. Day was also keenly interested in birds, knew most of the local species very well, though he did no special work in ornithology.My experiences with him in the field leads me to put full trust in his bird identifications, a trust I see no reason even at this late date, •o question.--W.H. BERGTOLD, Denver, Colo.Arctic Three-toed Woodpecker at Guelph, Ontario.--OnNovember 20, 1926, within the city limits of Guelph, Ontario, my attention was directed by a loudly repeated bird-call which I immediately recognized as
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 | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".