Use of DNA barcode in the identification of fish species from Ribeira de Iguape Basin and coastal rivers from São Paulo State (Brazil)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it