{"id":"W2554883894","doi":"10.1007/s10750-016-3054-6","title":"Strategies to avoid the trap: stream fish use fine-scale hydrological cues to move between the stream channel and temporary pools","year":2016,"lang":"en","type":"article","venue":"Hydrobiologia","topic":"Fish biology, ecology, and behavior","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Fundação de Amparo à Pesquisa do Estado do Amazonas; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Natural Sciences and Engineering Research Council of Canada; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Habitat; Channel (broadcasting); STREAMS; Environmental science; Ecology; Stream restoration; Movement (music); Spatial ecology; Fish <Actinopterygii>; Fishery; Biology; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0005032204,0.0003237845,0.0003328015,0.00003515577,0.0003452237,0.00008544211,0.0007245186,0.0003112856,0.0004582478],"category_scores_gemma":[0.0001250954,0.0001352805,0.000088802,0.0001956377,0.0009761339,0.0002360481,0.0006114571,0.0002408336,0.0003821831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006424027,"about_ca_system_score_gemma":0.00001493996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003780336,"about_ca_topic_score_gemma":0.001721622,"domain_scores_codex":[0.9979354,0.0002836573,0.0003329533,0.0006989137,0.0001164475,0.0006326833],"domain_scores_gemma":[0.9985073,0.0006751852,0.00009668277,0.0005223387,0.00001087179,0.0001876224],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006241621,0.0001130521,0.9278302,0.00000248625,0.00002766049,0.00001026092,0.0002422015,0.00008056264,0.04250704,0.00002124226,0.02393522,0.005167605],"study_design_scores_gemma":[0.0002381778,0.0007711403,0.9897119,0.00001104219,0.00002832337,0.00001312273,0.0003083145,0.000009850568,0.002813471,0.0004806369,0.005345751,0.0002682278],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9867617,0.0000187868,0.00005655045,0.01095294,0.0001367289,0.0007946019,0.0003777831,0.0001057199,0.0007951716],"genre_scores_gemma":[0.9963405,0.00002901918,0.0001272757,0.002444075,0.0001326553,0.0001444728,0.00002784494,0.00001524052,0.0007388809],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0618817,"threshold_uncertainty_score":0.5516579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02793903116581569,"score_gpt":0.2455971449461019,"score_spread":0.2176581137802862,"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."}}