Sex Determination of Least Sandpiper<i>(Calidris minutilla)</i>and Western Sandpiper (<i>Calidris mauri</i>): Comparing Methodological Robustness of Two Morphometric Methods
Bibliographic record
Abstract
Least (Calidris minutilla, n = 110) and Western (Calidris mauri, n = 37) sandpipers collected in Cuban wetlands were sexed by gonadal examination on dissection and used to assess the robustness of two morphometric methods commonly used to assign sex in shorebirds. Discriminant function analyses were performed and then tested by jackknife validation. The best discriminant function for Least Sandpiper included culmen and wing lengths and correctly classified 91% of the birds. Using culmen length, the discriminant function correctly sexed 97% of the Western Sandpiper. Sex ratio and morphometric estimates obtained through sexing Least and Western sandpipers by discriminant functions were not significantly different from the population sexed by gonadal examination on dissection. The range of the bill lengths used for sex determination of Least and Western sandpipers were then assessed by fitting the known-sex data. Classification accuracy of the bill length method was high for Western Sandpiper (95%), but was imprecise (44%) and female biased for Least Sandpiper. Consequently, a female biased sex ratio and under-estimation of male culmen length occurred for Least, but not Western, sandpipers classified by the bill length method. The findings suggest that sex determination based on the single measurement of culmen length is only accurate for Western Sandpiper, a species with high sexual size dimorphism. Linear measurements are also important for sex assignment in Least Sandpiper, but only using a discriminant function analysis approach.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".