Linking adults and immatures of South African marine fishes
Bibliographic record
Abstract
The early life-history stages of fishes are poorly known, impeding acquisition of the identifications needed to monitor larval recruitment and year-class strength. A comprehensive database of COI sequences, linked to authoritatively identified voucher specimens, promises to change this situation, representing a significant advance for fisheries science. Barcode records were obtained from 2526 early larvae and pelagic eggs of fishes collected on the inshore shelf within 5 km of the KwaZulu-Natal coast, about 50 km south of Durban, South Africa. Barcodes were also obtained from 3215 adults, representing 946 South African fish species. Using the COI reference library on BOLD based on adults, 89% of the immature fishes could be identified to a species level; they represented 450 species. Most of the uncertain sequences could be assigned to a genus, family, or order; only 92 specimens (4%) were unassigned. Accumulation curves based on inference of phylogenetic diversity indicate near-completeness of the collecting effort. The entire set of adult and larval fishes included 1006 species, representing 43% of all fish species known from South African waters. However, this total included 189 species not previously recorded from this region. The fact that almost 90% of the immatures gained a species identification demonstrates the power and completeness of the DNA barcode reference library for fishes generated during the 10 years of FishBOL.
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.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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 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".