Estimation of Muscle Mass by Ultrasonography Differs between Observers and Life States of Models in Small Birds
Bibliographic record
Abstract
Ultrasonography has proven to be a valuable noninvasive method of measure of muscle size in birds, but validation of its use in birds as small as black-capped chickadees (Poecile atricapillus; 11 g) is scarce. The effect of observers and life state (dead or alive) of models used for calibration on measurement quality is also poorly documented. Using 31 dead and 22 live chickadees, linear regressions between ultrasound and dissection measurements of pectoral and thigh muscles were fitted and compared between five different observers. R(2) values varied greatly between observers and were generally weaker in live birds, ranging between 0.02 and 0.59, despite high repeatability of measurement. Using equations calculated from dead birds to estimate muscle mass of live birds yielded much higher measurement errors (9%-18%) than when using equations calculated from live birds (5%-8%). Our results suggest that with careful training and using only calibration from live birds, ultrasonography can be a useful but limited tool to estimate muscle size of birds as small as the black-capped chickadee.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".