{"id":"W4376115590","doi":"10.1242/jeb.246001","title":"ECR Spotlight – Jeffrey Hainer","year":2023,"lang":"en","type":"article","venue":"Journal of Experimental Biology","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Variety (cybernetics); Fish <Actinopterygii>; Selection (genetic algorithm); Experimental biology; Diversity (politics); Cognitive science; Biology; Psychology; Neuroscience; Sociology; Computer science; Anthropology; Artificial intelligence; Computational biology; Fishery","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003780137,0.0004829986,0.0004397895,0.0008011585,0.002362482,0.003930472,0.0008200599,0.002999377,0.04196556],"category_scores_gemma":[0.01148835,0.0003852329,0.0002441194,0.0005353951,0.001354723,0.003092263,0.002045226,0.00466901,0.02310636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002642309,"about_ca_system_score_gemma":0.003298403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007050093,"about_ca_topic_score_gemma":0.01337743,"domain_scores_codex":[0.9963655,0.0005236822,0.0001370564,0.0005752881,0.002117339,0.00028111],"domain_scores_gemma":[0.9875665,0.00153091,0.0004655748,0.0004955135,0.005893051,0.004048396],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001175584,0.000007805666,0.00005767891,0.0000178361,0.000001162303,0.00006159048,0.0001035515,0.00001226987,0.0002232584,0.001078655,0.9903455,0.008078816],"study_design_scores_gemma":[0.000001535182,0.000009788431,0.0002789809,0.00003754183,5.523214e-7,0.0001598779,0.0002295848,0.00002356452,0.0001225789,0.0002687251,0.9988602,0.000007021892],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.0036517,0.0450002,0.001705965,0.6415086,0.1520854,0.00007737943,0.000485563,0.0005512438,0.154934],"genre_scores_gemma":[0.01967166,0.01150338,0.001179738,0.1381921,0.01773481,0.00005910239,0.0002370806,0.0005142371,0.8109077],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.04196556,"threshold_uncertainty_score":0.1403887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01388997733281917,"score_gpt":0.270159062889534,"score_spread":0.2562690855567148,"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."}}