Chemical communication in the European otter, Lutra lutra
Bibliographic record
Abstract
European otter (Lutra lutra) scent marks (spraint and anal sac secretion material) from captive and wild animals were analysed using solvent extraction and solid phase micro extraction (SPME). An ageing study (using SPME) mapped spraint chemical composition changes following deposition and how low temperature storage and exposure to the environment affected these changes. Chemicals with opposite time dependence were found; providing a possible spraint ageing mechanism. Temperature and environmental conditions affected the rates of production and deterioration of these chemicals and therefore the accuracy of spraint age estimations. Identification of the fatty acid content of otter scent marking material from 4 otter species led to both intra-specific (L.lutra) and inter-specific (Canadian river, Lontra canadensis; Asian short claw, Aonyx cinerea; and Giant, Pteronura brasiliensis) comparisons. Low volatility fatty acids (C10-C24.1) were found in all scent mark types. Intra-specifically, differentiation was seen in spraint fatty acid profiles based on sexual identity. Differentiation was observed between L. lutra scent marking material types (Captive spraint; Wild spraint; Wild anal sac secretion). Inter-specific differences relied on a mixture of ?digital? and ?analogue? coding. SPME and gas chromatography ? mass spectrometry (GCMS) were used to investigate intra- (L.lutra) and inter- specific (L. lutra, A. cinerea, L. canadensis, and badger, Meles meles) differences in the headspace chemicals of otter scent marks. Inter-sanctuary (possibly diet related) differences in spraint odour of L. lutra were seen. No overall male - female differences were found, although possible intra-sanctuary sexual differences were seen. Inter-specific differentiation in scent mark odour profiles due to a combination of both analogue and digital coding elements was observed
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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) | 0.003 | 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".