Morphological Variation of Coilia Mystus (Clupeiformes: Engraulidae) in Three Chinese Estuaries
Bibliographic record
Abstract
Truss network data were collected and investigated in order to clarify the morphological variation in populations of Coilia mystus from three Chinese estuaries. Nineteen morphometric measurements were made for each individual, and Burnaby's multivariate method was used to obtain size-adjusted shape data. The cluster analysis and discriminant analysis were used to discriminate morphological differences among populations. The results indicated that 1) the three populations were clustered into two distinct groups: the first group included Changjiang C. mystus and Zhujiang C. mystus, the last one included Minjiang C. mystus, and 2) discriminant analysis with selected 5 morphological parameters showed that the identification accuracy was between 98.7952% and 100%, and global identification accuracy was 99.2933%. Reproductive isolation and adaption to environmental condition are determinant factors for morphological variation between populations of C. mystus.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".