{"id":"W3200413515","doi":"10.3389/fevo.2021.723026","title":"‘Taking Fishers’ Knowledge to the Lab’: An Interdisciplinary Approach to Understand Fish Trophic Relationships in the Brazilian Amazon","year":2021,"lang":"en","type":"article","venue":"Frontiers in Ecology and Evolution","topic":"Isotope Analysis in Ecology","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Universidade Federal do Rio Grande do Sul; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Social Sciences and Humanities Research Council of Canada; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Trophic level; Isotope analysis; Amazon rainforest; Ecology; Food web; Biology; Fishery; Mesopredator release hypothesis; Ecosystem; Apex predator","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003182264,0.0003082805,0.0003747049,0.003694667,0.002485147,0.001517541,0.0008772969,0.0006045509,0.001664388],"category_scores_gemma":[0.004364854,0.0003742595,0.0003655227,0.001847697,0.002538007,0.003849738,0.002537744,0.0005470648,0.0001220612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003003505,"about_ca_system_score_gemma":0.005308178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07295709,"about_ca_topic_score_gemma":0.1932621,"domain_scores_codex":[0.998984,0.0004568176,0.0000862252,0.0001777688,0.0001472097,0.0001479107],"domain_scores_gemma":[0.9979442,0.000872894,0.000354759,0.0001789888,0.0003185901,0.0003306314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008874548,0.0001238237,0.4292811,0.0006177916,0.00006861782,0.00153882,0.2182465,0.0005516779,0.006842077,0.008407998,0.001882131,0.3323508],"study_design_scores_gemma":[0.00002003021,0.0001099969,0.6402736,0.001008464,0.00008062591,0.001033122,0.2949953,0.003745124,0.001244434,0.01786933,0.03954019,0.00007966068],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9535365,0.003896042,0.01373851,0.01229268,0.00004612166,0.000152598,0.0002099312,0.00003894771,0.01608866],"genre_scores_gemma":[0.984248,0.001470446,0.01265926,0.0004227418,0.0000137095,0.00007194156,0.00005992798,0.000007020225,0.001046902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07295709,"threshold_uncertainty_score":0.1450649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02047722715000373,"score_gpt":0.2592520016046989,"score_spread":0.2387747744546951,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}