Bibliographic record
Abstract
Ninety-two of the 98 compilers sub¬ mitting Christmas Bird Counts (CBC) also sent in mammal counts.The 34 species of mammals seen or heard on count day was second only to the 35 seen or heard in 2003, while the 4360 individuals is the most since overall to¬ tals were first tabulated in 2002.As usual, the most abundant mam¬ mal was the White-tailed Deer, followed by the Mule Deer.For the first time in at least four years, the Pronghorn outnum¬ bered the American Red Squirrel and took third place.The most frequentlyseen mammals have involved the same four species since 2002.This year, White-tailed Deer were noted on 70% of all counts, American Red Squirrels on 59%, Coyotes on 58%, and Mule Deer on only 30%.Estuary had the most species seen in a day at 10, (followed by Skull Creek and Swift Current, each with 9) while Fort Walsh had the most individuals with 431.Although all-time high counts for each species have yet to be tabulated, some of this year's counts must be con¬ tenders.These include 37 Eastern Grey Squirrels from Swift Current, 71 Meadow Voles from Somme, and 9 moose from Kindersley North.No new species were recorded, but the Bison due to be released into the wild in Grasslands National Park may qualify next year.Rarities included a Swift Fox seen on the Govenlock count and tracks of Mountain Lion noted in the Cy¬ press Hills on both the Fort Walsh and Cypress Hills Provincial Park counts.For information on participants, weather, coverage and location of Christ¬ mas Mammal Counts, see the CBC summary in this issue.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.100 | 0.039 |
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".