Bibliographic record
Abstract
General 2Votes.•0 9 I have, I presume, some 3000 individuals in the pond.I first observed this evidence of destruction early in May last, and it was not until late in July that I detected the cause of it.Large flocks of ,•tdscalus g. ieuetts make.their home annually fi'om early sp•-ing till late every fall, in the pine, spruce and hemlock groves which belong to my grounds; as I do not raise cereals, and devote my [and to fruit culture, I regard these birds as the most valuable of their kind to me, and never have permitted them to be shot at or disturbed on my premises.Going do•vn to my pond.as usual, in quest of Kingfishers, I happened to take notice of a Crow Blackbird in the act of striking quickly with its bill into the water at the edge of the bank.Wondering what it found there for food, I cautiuusly approached, sneaking behind the shelter of au evergreen and bed offloweriag shrubs.This bird had strucka small goldfish
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.839 | 0.550 |
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".