{"id":"W4394189541","doi":"10.6084/m9.figshare.23518962","title":"Bayesian Modeling and Inference for One-Shot Experiments","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research","funders":"","keywords":"Inference; Bayesian inference; Bayesian probability; Shot (pellet); Econometrics; Computer science; Artificial intelligence; Machine learning; Statistics; Mathematics; Chemistry","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":[0.05359936,0.001928302,0.002918011,0.002520096,0.0009890491,0.00360193,0.005277833,0.004433405,0.02195895],"category_scores_gemma":[0.1908357,0.001057373,0.003728292,0.003702566,0.001951995,0.00250524,0.002265672,0.004690543,0.007289882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00256102,"about_ca_system_score_gemma":0.002668309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006563086,"about_ca_topic_score_gemma":0.01035953,"domain_scores_codex":[0.9709005,0.02366188,0.001345598,0.002699167,0.0011097,0.0002830661],"domain_scores_gemma":[0.8722429,0.1087087,0.004278196,0.01202832,0.002266149,0.0004757225],"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":[0.003018907,0.0003298456,0.02096282,0.007363193,0.003477814,0.0005453951,0.0005663818,0.1629273,0.0008957236,0.1395719,0.4704132,0.1899276],"study_design_scores_gemma":[0.002816612,0.000204323,0.007464297,0.001014865,0.000915929,0.0005957035,0.00009197094,0.2518942,0.0009626314,0.5773669,0.1564782,0.000194381],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"dataset","genre_scores_codex":[0.01034869,0.006064618,0.7458321,0.007853418,0.0005430687,0.001626647,0.2162544,0.006005808,0.005471373],"genre_scores_gemma":[0.1537725,0.002983219,0.6409,0.006057447,0.0005290405,0.01645194,0.1714245,0.001839029,0.006042319],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.05359936,"threshold_uncertainty_score":0.2834639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8959912511485137,"score_gpt":0.6434976447272281,"score_spread":0.2524936064212856,"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."}}