{"id":"W2522004779","doi":"10.25334/q4sx15","title":"Datasets for Whitlock &amp; Schluter's \"The Analysis of Biological Data\"","year":2018,"lang":"en","type":"article","venue":"QUBES","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"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":[],"consensus_categories":[],"category_scores_codex":[0.0005536738,0.00009417356,0.0001674079,0.00006682042,0.00009058116,0.00002348267,0.0008575316,0.0001247979,0.00008681336],"category_scores_gemma":[0.0006349853,0.00005605902,0.00009122877,0.0002039601,0.000536365,0.000003410828,0.0005269631,0.00004698892,0.00002908551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003250458,"about_ca_system_score_gemma":0.00005104066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002771085,"about_ca_topic_score_gemma":0.0003761551,"domain_scores_codex":[0.9990265,0.00003888485,0.0002570372,0.0002570297,0.0001770227,0.0002434785],"domain_scores_gemma":[0.9986262,0.00005517578,0.00006694217,0.001029098,0.0001412363,0.00008137603],"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":[0.0005157767,0.0004876839,0.01344594,0.0001711966,0.00355672,8.430247e-7,0.00027657,0.00001449962,0.292401,0.000238658,0.6195322,0.06935885],"study_design_scores_gemma":[0.000375243,0.0005708574,0.01096473,0.000007957004,0.0003028584,0.000001897989,0.0001336776,0.002497922,0.04667132,0.0001148016,0.9381815,0.0001772287],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9651071,0.0007192661,0.02404758,0.00105013,0.0002810502,0.0004516972,0.007734643,0.00001309302,0.0005954803],"genre_scores_gemma":[0.9764035,0.0004190993,0.006302244,0.0004759375,0.0005126177,0.00001512983,0.01553663,0.000008323841,0.0003265335],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3186493,"threshold_uncertainty_score":0.228602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08185099069105624,"score_gpt":0.3688933378980567,"score_spread":0.2870423472070005,"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."}}