DNA barcoding reveals overlooked marine fishes
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
With more than 15 000 described marine species, fishes are a conspicuous, diverse and increasingly threatened component of marine life. It is generally accepted that most large-bodied fishes have been described, but this conclusion presumes that current taxonomic systems are robust. DNA barcoding, the analysis of a standardized region of the cytochrome c oxidase 1 gene (COI), was used to examine patterns of sequence divergence between populations of 35 fish species from opposite sides of the Indian Ocean, chosen to represent differing lifestyles from inshore to offshore. A substantial proportion of inshore species showed deep divergences between populations from South African and Australian waters (mean = 5.10%), a pattern which also emerged in a few inshore/offshore species (mean = 0.84%), but not within strictly offshore species (mean = 0.26%). Such deep divergences, detected within certain inshore and inshore/offshore taxa, are typical of divergences between congeneric species rather than between populations of a single species, suggesting that current taxonomic systems substantially underestimate species diversity. We estimate that about one third of the 1000 fish species thought to bridge South African and Australian waters actually represent two taxa.
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