{"id":"W2963540106","doi":"10.1111/mec.15184","title":"Amazon fish bacterial communities show structural convergence along widespread hydrochemical gradients","year":2019,"lang":"en","type":"article","venue":"Molecular Ecology","topic":"Microbial Community Ecology and Physiology","field":"Environmental Science","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Instituto Chico Mendes de Conservação da Biodiversidade; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Instituto Nacional de Pesquisas da Amazônia; Natural Sciences and Engineering Research Council of Canada; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Fonds de recherche du Québec – Nature et technologies; Université Laval","keywords":"Biology; Amazon rainforest; Fish <Actinopterygii>; Convergence (economics); Ecology; Fishery","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001589358,0.0002088016,0.0003157599,0.00003487785,0.0001813046,0.00001521022,0.0007291311,0.0002848979,0.04150777],"category_scores_gemma":[0.00003717756,0.0002197117,0.00009052633,0.0001029119,0.0005440476,0.000118404,0.0007959948,0.0004393152,0.001646518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001171424,"about_ca_system_score_gemma":0.00001712443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007829592,"about_ca_topic_score_gemma":0.006697797,"domain_scores_codex":[0.9983969,0.0005161538,0.000245679,0.0002624218,0.00008747491,0.0004913784],"domain_scores_gemma":[0.9990478,0.0001923103,0.0000989472,0.0005583459,0.00001157152,0.00009102059],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001223825,0.00006756282,0.3510831,0.00001109894,0.00004458067,0.0000231108,0.0005677921,0.0003132896,0.643168,0.0002677599,0.004221612,0.0001096883],"study_design_scores_gemma":[0.002191487,0.001042654,0.8650194,0.00001762595,0.00006297902,0.0001876959,0.000316909,0.001406255,0.1048296,0.00570306,0.01824174,0.0009806097],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957825,0.000005677278,0.00001265859,0.0002347417,0.001076357,0.0002657235,0.00001803739,0.00004168744,0.002562642],"genre_scores_gemma":[0.9972407,0.000006009952,0.0001454906,0.001991562,0.00002323096,0.00001245171,0.0003244843,0.00001778915,0.0002382588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5383384,"threshold_uncertainty_score":0.9991308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005605699550449097,"score_gpt":0.2040987493719565,"score_spread":0.1984930498215075,"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."}}