Bibliographic record
Abstract
that birds seldom vary on account of the season more than six days either way from their average date of arrival.An example will show how this limit of six days is employed.The Hooded Warbler has been reported as arriving at Washington, D.C., on the following dates during fifteen .differentyears: April 19, 26, 27, 27, 29, 29, 30, May 1, 1, 3, 6, 8, 9, 10, 12.The average of these fifteen dates as they stand is May 2. The first rejection drops April 19 as too early, and May 9, 10, and 12 as too late.The average of the remaining dates is May 1.It is now seen that May 8, should also be discarded.The average of the ten dates left is April 30.This date of April 30 is considered as the "probable normal date of arrival," so far as our records stand at the present timc, and is published as the "average date of spring arrival" based on ten years' records.How near this date is to the truth can be surmised from the amount of variation in the records.The differences between each of the ten dates used and April 30 is, in days, as follows; 4, 3, 3, 1, 1, 0, 1, 1, 3, total of 23, which divided by ten gives 2.3 days as the probable error; i.e., it is probable that the (late April 30 is within 2.3 (lays of correct.The greater the number of observations and the closer these are in agreemeat, the smaller will be the probable en'or.Thus in the case of the White-eyed Vireo at Washington, D.C., the earliest dates of arrival for t•venty-two years are: April 18, 18, 19, 19, 20, 21, 21, 22, 22, 22, 22, 23, 23, 23, 24, 24, 24, 25, 25, 26, 26, 26 --average, April 23; average variation from this date, 2.1 days.The most uniform record we have in all our four hundred thousand notes on bird migration is that of the Chimney Swift at New Market, Va.The dates of arrival are: April 10, 11, 11, 12,
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.636 | 0.205 |
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".