Use of DNA barcode in the identification of fish species from Ribeira de Iguape Basin and coastal rivers from São Paulo State (Brazil)
Bibliographic record
Abstract
Abstract Species identification is a difficult task, ranging from the definition of the species concept itself to the definition of the threshold for speciation. DNA Barcode technology uses a fragment of the Cytochrome Oxidase I (COI) gene as a molecular tool that many studies have already validated as a tool for species identification. DNA barcode sequences for COI were generated and analyzed from 805 specimens. The General Mixed Yule Coalescent (GMYC) analysis recognized 99 independent evolution units, and the Barcode Index Numbers (BIN) approach pointed to the existence of 104 BINs (interpreted as distinct species). By cross-tabulating the results of all approaches, we identified 109 Molecular Operational Taxonomic Units (MOTU) by at least one methodology. In most cases (89 MOTUs), the genetic approaches are in agreement with morphological identification, and the discrepant results of MOTUs are in the complex groups, which have many morphological similarities but may represent species complexes.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".