<scp>DNA</scp> barcodes identify marine fishes of <scp>S</scp>ão <scp>P</scp>aulo <scp>S</scp>tate, <scp>B</scp>razil
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
Anthropogenic impacts are an increasing threat to the diversity of fishes, especially in areas around large urban centres, and many effective conservation actions depend on accurate species identification. Considering the utility of DNA barcoding as a global system for species identification and discovery, this study aims to assemble a DNA barcode reference sequence library for marine fishes from the coastal region of São Paulo State, Brazil. The standard 652 bp 'barcode' fragment of the cytochrome c oxidase subunit I (COI) gene was PCR amplified and bidirectionally sequenced from 678 individuals belonging to 135 species. A neighbour-joining analysis revealed that this approach can unambiguously discriminate 97% of the species surveyed. Most species exhibited low intraspecific genetic distances (0.31%), about 43-fold less than the distance among species within a genus. Four species showed higher intraspecific divergences ranging from 2.2% to 7.6%, suggesting overlooked diversity. Notably, just one species-pair exhibited barcode divergences of <1%. This library is a first step to better know the molecular diversity of marine fish species from São Paulo, providing a basis for further studies of this fauna - extending the ability to identify these species from all life stages and even fragmentary remains, setting the stage for a better understanding of interactions among species, calibrating the estimations about species composition and richness in an ecosystem, and providing tools for authenticating bioproducts and monitoring illegal species exploitation.
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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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