{"id":"W195255639","doi":"10.1023/a:1025762314250","title":"Zebra Fish: An Uncharted Behavior Genetic Model","year":2003,"lang":"en","type":"article","venue":"Behavior Genetics","topic":"Zebrafish Biomedical Research Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":232,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Biology; ZEBRA (computer); Model organism; Fish <Actinopterygii>; Genetics; Genetic screen; Vertebrate; Evolutionary biology; Identification (biology); Zoology; Gene; Ecology; Mutant; Fishery; Computer science","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000168967,0.0002847753,0.0001833304,0.00008974935,0.0001696716,0.00006799024,0.0005547329,0.000347467,0.0001818258],"category_scores_gemma":[0.0001123725,0.0003024191,0.000119379,0.0002388389,0.0002570929,0.000005926487,0.0001327297,0.0002064295,0.00006505061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003485615,"about_ca_system_score_gemma":0.0003281351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001063576,"about_ca_topic_score_gemma":0.00009456852,"domain_scores_codex":[0.9976667,0.0001147717,0.0003719507,0.00071518,0.0004863096,0.0006451028],"domain_scores_gemma":[0.9978704,0.000009535823,0.00007976446,0.00118513,0.0002261236,0.000629071],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000147775,0.0009807532,0.02091602,0.000007099042,0.00001786093,0.00001800151,0.00002674345,0.0001535791,0.9589602,0.0002194328,0.004360044,0.0143255],"study_design_scores_gemma":[0.002378359,0.001518575,0.1562053,0.00001170101,0.0003732177,0.0001672989,0.000206481,0.003238049,0.734984,0.000425137,0.09896973,0.00152215],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9882907,0.0003035841,0.009553757,0.00009044576,0.00009314892,0.0008544168,0.0001863135,0.00005006507,0.0005775607],"genre_scores_gemma":[0.9737777,0.0002624018,0.02281408,0.0005405507,0.0001164212,0.001005755,0.0004861093,0.00009234256,0.0009046394],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2239762,"threshold_uncertainty_score":0.9999428,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03357785876609982,"score_gpt":0.3269164403925561,"score_spread":0.2933385816264563,"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."}}