Bibliographic record
Abstract
HistoryAn adult 4-kg (8.8-lb) female Canada Goose (Branta canadensis) was brought in to the veterinary clinic for evaluation after being found injured and on the side of the road.The cause of injuries was unknown; the bird had abrasions on the left side of its body over the elbow joint, tarsometatarsus, and metatarsophalangeal joint.The area over the left tarsometatarsus was edematous and warm to the touch.The goose had slow withdrawal reflexes in the left pelvic limb and was unable to stand because of paresis of the left pelvic limb.Left lateral and ventrodorsal radiographic views of the whole body were obtained from which close-up radiographic images of the thoracic limbs (humeri) and left tarsometatarsus, respectively, were evaluated (Figure 1).Determine whether additional imaging studies are required, or make your diagnosis from Figure 1-then turn the page →
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.015 | 0.008 |
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".