{"id":"W4400884481","doi":"10.1080/23308249.2024.2374964","title":"Advancements in Riverine Fish Movement Modeling: Bridging Environmental Complexity and Fish Behavior","year":2024,"lang":"en","type":"article","venue":"Reviews in Fisheries Science & Aquaculture","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Great Lakes Fishery Commission","keywords":"Bridging (networking); Fish <Actinopterygii>; Movement (music); Computer science; Consistency (knowledge bases); Scale (ratio); Range (aeronautics); Environmental resource management; Environmental science; Ecology; Fishery; Geography; Engineering; Artificial intelligence; Cartography; Biology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001786217,0.001004495,0.001231852,0.001363042,0.0003986643,0.002271291,0.00185644,0.001340693,0.002145812],"category_scores_gemma":[0.005717557,0.000471572,0.001536725,0.002332428,0.000967538,0.003345981,0.002050877,0.001415245,0.0005142005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000827363,"about_ca_system_score_gemma":0.001811275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01196323,"about_ca_topic_score_gemma":0.01033258,"domain_scores_codex":[0.9992617,0.0003084345,0.00007759578,0.0001730045,0.0001484943,0.00003072649],"domain_scores_gemma":[0.9972185,0.001949884,0.0003505331,0.0001624026,0.0002581397,0.0000606041],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005749593,0.0001607544,0.02388374,0.00758914,0.0008079522,0.0002401112,0.0009299504,0.5465996,0.002294079,0.09136584,0.005970394,0.320101],"study_design_scores_gemma":[0.00002756183,0.0001961084,0.01544483,0.004787417,0.0007017756,0.0002510555,0.001004228,0.6521384,0.001268225,0.1539539,0.1700233,0.0002032132],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.05992218,0.1650002,0.7318358,0.01022673,0.0006897627,0.0001574924,0.002256892,0.0005845104,0.02932642],"genre_scores_gemma":[0.5166177,0.2796167,0.1914715,0.001542018,0.001073723,0.0006651692,0.002660662,0.0003522389,0.006000275],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01196323,"threshold_uncertainty_score":0.02378714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04055635260322971,"score_gpt":0.2736264348755287,"score_spread":0.233070082272299,"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."}}