Field Identification of the Mice <em>Peromyscus leucopus noveboracensis</em> and <em>P. maniculatus gracilis</em> in Central New York
Bibliographic record
Abstract
Field identification of the White-footed Mouse (Peromyscus leucopus noveboracensis) and Long-tailed Deer Mouse (Peromyscus maniculatus gracilis) is difficult because of their similar external morphology. Peromyscus were sampled by live-trapping during a five-year period (1992-1996) at the Arnot Teaching and Research Forest, Van Etten, New York and identified to species by electrophoresis of their salivary amylase. No electromorphs were shared between P. leucopus and P. maniculatus, thus permitting unambiguous species identification of individuals. Means and ranges of four external measurements (ear, head-body, hind-foot, and tail) and tail to head-body ratio were determined for amylase-genotyped live mice. Although some body measurements did differ on average between the two species (ear, head-body, and tail for adults; hind-foot and tail for juveniles), the ranges of these overlap considerably. When the four external measurements (excluding the tail to head-body ratio) were used to construct two discriminant-function equations, they yielded correct identification of 80% of the adult P. l. noveboracensis and P. m. gracilis assessed excluding juveniles, and 71% of adult and juvenile mice combined. The function reported here allows partial field identification, but genetic analysis remains the only reliable field method for differentiation between live P. l. noveboracensis and P. m. gracilis. Includes erratum for a figure in this article.
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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 | 0.000 |
| 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) | 0.002 | 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".