{"id":"W4380081976","doi":"10.1093/jrssig/qmad042","title":"Data at the Ballet","year":2023,"lang":"en","type":"article","venue":"Significance","topic":"Dietary Effects on Health","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Ottawa Mental Health Centre","funders":"","keywords":"Ballet; Analytics; Art; Visual arts; Data science; Computer science; Dance","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01085516,0.0007295882,0.001183382,0.004400169,0.002347106,0.00830507,0.002186213,0.003890162,0.2287744],"category_scores_gemma":[0.1038047,0.0009419686,0.00140943,0.006269849,0.001450222,0.005328279,0.006747476,0.006461288,0.1228651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002486836,"about_ca_system_score_gemma":0.005703276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01239694,"about_ca_topic_score_gemma":0.009022909,"domain_scores_codex":[0.9870756,0.003056135,0.001222527,0.002160741,0.005521736,0.0009632338],"domain_scores_gemma":[0.9472503,0.01918984,0.003124176,0.01203552,0.01439003,0.0040102],"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":[0.0002842313,0.00003070617,0.002870216,0.0002488983,0.0000304315,0.0001292071,0.0002634819,0.000188609,0.0002359949,0.007753711,0.9526425,0.03532201],"study_design_scores_gemma":[0.00006113562,0.00003584076,0.003317946,0.0003905799,0.00001546059,0.0001029309,0.0002268539,0.0003046854,0.0003885009,0.006851222,0.9882598,0.00004499538],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.01076609,0.003571316,0.02153747,0.1734309,0.02508535,0.001234447,0.5691327,0.01598551,0.1792562],"genre_scores_gemma":[0.1245193,0.003964758,0.04507932,0.07186574,0.008551403,0.003265622,0.4433056,0.01301389,0.2864343],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2287744,"threshold_uncertainty_score":0.7653267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1114057736069896,"score_gpt":0.3746567028962654,"score_spread":0.2632509292892758,"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."}}