From ethnobiology to ecotoxicology : fishers’ knowledge on trophic levels as indicator of bioaccumulation in tropical marine and freshwater 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
Agradecimentos: We thank fishers for their cooperation, L.C.F. Porcher, P.P. Nitschke, and T.A. Solaro for helping with data organization, and Z. Castilhos for advice on mercury data. We thank an anonymous reviewer for useful suggestions. The research projects were funded by Centrais Elétricas do Norte do Brasil S/A (Eletronorte) (Contract 4500057477, ELN/ANEEL/ FAURGS, Tocantins River), Fundação de Amparo a Pesquisa do Estado de São Paulo (FAPESP, Brazilian coast and Negro River), International Development Research Centre (IDRC, Canada) Grant (# 104519-004, Paraty, southeastern Brazilian coast). R.A.M.S (304377/2010-4), and A.B. acknowledge research grants (309014/2013-1) and financial support to present this research in a meeting (AVG 457348/2012-7) from the Conselho Nacional de Desenvolvimento Científico and Tecnológico (CNPq)
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 | 0.001 | 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