Identification and field testing of sex-attractant semiochemicals produced by male deer mice, <i>Peromyscus maniculatus</i>
Bibliographic record
Abstract
Following previous reports that male deer mice, Peromyscus maniculatus , produce chemical signals that attract conspecific females, we analysed and field-tested sex-attractant semiochemicals (message-bearing chemicals) of male deer mice. Field traps baited with urine- and faeces-soiled bedding of male mice captured adult female, but not male, mice, indicating dissemination of sex-attractant semiochemicals from the males’ excreta. Analysing excreta headspace volatiles of both males and females by gas chromatography–mass spectrometry revealed that 5-methyl-2-hexanone was male-specific, and that eight other ketones (3-methyl-2-pentanone, 2-hexanone, 4-heptanone, 2-heptanone, 6-methyl-2-heptanone, 3-octanone, 2-octanone, 2-nonanone) were 2.6–5.6 times more abundant in male, than in female, samples. In a field experiment with paired trap boxes, treatment boxes baited with the synthetic ketone lure captured 3.4 times more females (17 : 5) and 1.6 times fewer males (5 : 8) than corresponding unbaited boxes. In a follow-up paired-trap field experiment, treatment boxes baited with both the ketone lure and synthetic testosterone captured 8 times more mature females and 2.3 times more immature females, but 9 times fewer immature males, than control boxes baited only with the ketone lure, all indicating that testosterone is a synergistic sex-attractant semiochemical. As previously shown in house mice, Mus musculus , and brown rats, Rattus norvegicus , sex-attractant semiochemicals of male deer mice comprise both volatile and sex steroid components.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".