{"id":"W3184283071","doi":"10.3389/fanim.2021.695054","title":"Data Driven Insight Into Fish Behaviour and Their Use for Precision Aquaculture","year":2021,"lang":"en","type":"article","venue":"Frontiers in Animal Science","topic":"Water Quality Monitoring Technologies","field":"Environmental Science","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Horizon 2020 Framework Programme; European Commission","keywords":"Aquaculture; Environmental science; Fish farming; Fish <Actinopterygii>; Exploit; Fishery; Environmental data; Computer science; Environmental resource management; Ecology; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002875858,0.0008257511,0.0004965154,0.003655732,0.0003974892,0.001806258,0.0009993135,0.0007632621,0.001612175],"category_scores_gemma":[0.01260022,0.0004535762,0.001207304,0.003260662,0.0007727885,0.001933571,0.001505149,0.001338914,0.0009203697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001152989,"about_ca_system_score_gemma":0.001482757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02836014,"about_ca_topic_score_gemma":0.06340542,"domain_scores_codex":[0.9986237,0.0003842138,0.0001356234,0.000353956,0.0004225514,0.00007987532],"domain_scores_gemma":[0.9919228,0.004635127,0.0008101455,0.001413719,0.001045145,0.0001730193],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004187376,0.0004523438,0.3889199,0.002199778,0.0006621737,0.0007747377,0.002852174,0.09795491,0.01859349,0.02018804,0.03802016,0.4289636],"study_design_scores_gemma":[0.00006606642,0.0002616445,0.3234457,0.0008536721,0.0001645183,0.0004789133,0.003346569,0.4082621,0.01486859,0.06213963,0.1858615,0.0002510721],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.176248,0.002183634,0.5325131,0.005654394,0.000245521,0.0006192686,0.252969,0.01900765,0.01055932],"genre_scores_gemma":[0.4284391,0.001407188,0.4111556,0.0007172127,0.0001175634,0.0005894547,0.1547503,0.0008894764,0.00193401],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02836014,"threshold_uncertainty_score":0.05639011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05226348175842395,"score_gpt":0.2873138295856905,"score_spread":0.2350503478272666,"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."}}