The bycatch of piramutaba, Brachyplatystoma vaillantii industrial fishing in a salinity and depth gradient in the Amazon estuary, 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 The piramutaba, Brachyplatystoma vaillantii is a freshwater catfish that is the most abundant fishery resource in the Amazon estuary. Piramutaba trawling is done on industrial fishing scale and is characterized by the presence of many freshwater and marine bycatch species, with and without commercial value. Here we describe the bycatch of the industrial fishery of piramutaba in the Amazon estuary and evaluate the relationship of two important environmental factors, depth and salinity, with the accidental capture of freshwater and marine fishes in the Amazon estuary in the rainy and dry seasons. We identified 21 cartilaginous fish species (19.1% freshwater and 80.9% marine) and 125 bony fish species (25.6% freshwater and 74.4% marine). The bycatch included 64 species without commercial value (43% of all bycatch species), which are always discarded. Freshwater and estuarine fishes exhibited significantly higher abundances in shallower environments, while marine fishes were similarly abundant along the entire depth gradient. On the contrary, the abundance of freshwater fishes significantly decreased, and that of estuarine and marine fishes significantly increased with increasing salinity. Regarding the conservation status of the bycatch species, one is classified as vulnerable (VU), and seven as critically endangered (CR). The information on the bycatch of piramutaba fishery in the Amazon estuary is important to subsidize regional fisheries policies and the management of protected areas.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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