Bibliographic record
Abstract
he late summer and fall is a time of transitional weather, and when one considers the huge size of the province of Ontario, just about every condition possible will likely occur.On the same day in mid-August, hot and humid conditions in southwestern Ontario contrasted sharply with the first snow of the approaching winter along the Hudson Bay coast far to the north.Summer tended to ease out slowly through most of the central and southern parts of the province, with enjoyable weather the rule.In the northwest, an unpleasant taste of winter arrived in mid-September, when a week of cold resulted in several inches of snow on the ground.Once the snow melted, a more setfled but slowly cooling trend was the rule for the majority of the province.The approach and arrival of Hurricane Isabel was the most anticipated weather event of the period (see the Special Report, this issue).Another anticipated event was the arrival of Cave Swallows in early November, again in the southern part of the province.The fall migration was rather unspectacular, and many birders commented on how birds just seemed to slip away, with low numbers and litde buildup in many cases.Of course, rare birds did turn up: Bandtailed Pigeons in Sudbury and London, a Rufous Hummingbird in Kingston, a Kentucky Warbler near Ihunder Bay, and a Ross's Gull in Point Pdee National Park were seen by birders from across the province.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.574 | 0.209 |
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".