Diagnostic features and biometry of head bones for identifying Carassius species in faecal and archaeological remains
Bibliographic record
Abstract
The identification of fish species from head bone remains is employed in various sciences, including archaeology, paleontology and field ecology, with the estimation of fish size from biometric relationships being useful in the assessment of predation pressure exerted by increasing numbers of piscivorous species (e.g. Eurasian otter Lutra lutra and great cormorant Phalacrocorax carbo). This is particularly relevant for crucian carp, Carassius carassius, which is in decline in Europe due to changes in land use and to increasing numbers of non-native Carassius species (i.e. goldfish C. auratus, gibel carp C. gibelio), which hybridize with C. carassius. However, diagnostic keys and biometric relationships are lacking for C. carassius and its most common hybrids, crosses with C. auratus. The present paper addresses this gap in knowledge, providing diagnostic keys and biometric relationships for the head bones of all Carassius species found in Europe as well as for C. carassius × C. auratus hybrids. All bone size to body length relationships were statistically significant. Similarly, all bone size to body weight relationships were significant for C. carassius, C. auratus, and C. gibelio, but none were significant for C. carassius × C. auratus hybrids. Diagnostic structures were found to distinguish easily between the Carassius species and hybrids, which will assist in determining the identity and sizes of prey found in faecal and archaeological remains.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".