INTRASPECIFIC IDENTIFICATION OF TRACHIDERMUS FASCIATUS(SCORPAENIFORMES,COTTIDAE)BASED ON TRUSS NETWORK DATA
Bibliographic record
Abstract
Truss network data were used in order to clarify the morphological differences of three extant populations of Trachidermus fasciatus in China.Twenty-two morphometric measurements were made for each individual.Burnaby's multivariate method was used to obtain size-adjusted shape data.The cluster analysis and discriminant analysis were used to discriminate among populations.The results indicated:1)the three populations were clustered into two distinct groups;the first group included the populations of T.fasciatus living in Qinglong He and in Fuchun Jiang,the last one included the population in Yalu Jiang;2)based on F-remove value,five morphological index,i.e.,D(2-3),D(7-9),D(6-5),D(6-8),and D(2-1),were selected into model.Discriminant analysis with these selected 5 morphological parameters showed that the identification accuracies were all 100 %.We concluded that these are three morphologically distinguishable populations of T.fasciatus.Reproductive isolation,genetic drift and environmental factors can cause diversification in body shape among different T.fasciatus populations.Though the present morphometric measurements discriminated the different populations of T.fasciatus,further verification of the population structure may be essential.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 teacher head, 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".