{"id":"W4288036951","doi":"10.3389/fmars.2022.851757","title":"Modeling the Probability of Overlap Between Marine Fish Distributions and Marine Renewable Energy Infrastructure Using Acoustic Telemetry Data","year":2022,"lang":"en","type":"article","venue":"Frontiers in Marine Science","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bedford Institute of Oceanography; Fisheries and Oceans Canada; Ocean Tracking Network; Acadia University; Dalhousie University","funders":"","keywords":"Tidal power; Marine energy; Environmental science; Renewable energy; Fishery; Telemetry; Morone saxatilis; Bass (fish); Species distribution; Bay; Oceanography; Ecology; Computer science; Habitat; Geology; Biology; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.001335468,0.000126598,0.0002110764,0.0000934105,0.0009154559,0.00002482146,0.001185561,0.00002721398,0.0004346851],"category_scores_gemma":[0.000283099,0.0001104594,0.00001821112,0.001200263,0.001204495,0.000310241,0.02096006,0.0002085196,1.842232e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003396648,"about_ca_system_score_gemma":0.00004745456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004922192,"about_ca_topic_score_gemma":0.003938201,"domain_scores_codex":[0.9982961,0.0000808649,0.0002821532,0.0005634319,0.0004086521,0.0003687415],"domain_scores_gemma":[0.9991198,0.00004826575,0.0001021256,0.0006667027,0.0000137701,0.00004940693],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00000957152,0.0000267338,0.7966387,0.000009497113,0.000009403081,0.000001301002,0.0000285206,0.1948029,0.00003814451,0.00003204822,0.003698176,0.004704977],"study_design_scores_gemma":[0.0001511687,0.00003027702,0.6954304,0.00000175018,0.00003019802,0.000002444188,0.0002721862,0.2865985,0.0000142035,0.01661202,0.0007507895,0.0001060745],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9703349,0.000006001292,0.02568148,0.0004580852,0.0003323273,0.0002725585,0.0001335294,0.00001903395,0.002762075],"genre_scores_gemma":[0.9666349,0.00003214925,0.03290012,0.0001462991,0.00001883144,0.00001860166,0.00007757241,0.000005598951,0.0001658771],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1012083,"threshold_uncertainty_score":0.9869583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01471431631092654,"score_gpt":0.2258865553583233,"score_spread":0.2111722390473967,"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."}}