{"id":"W4398995339","doi":"10.7910/dvn/zbrtjh/4nn65v","title":"Table2Sim2kLoadModules.R","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Replication (statistics); Inference; Root (linguistics); Unit root; Computer science; Econometrics; Statistics; Mathematics; Artificial intelligence; Philosophy; Linguistics","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002855095,0.003308058,0.002517203,0.004073429,0.00139764,0.004803594,0.005677373,0.002898444,0.3419351],"category_scores_gemma":[0.02476198,0.00135253,0.00266614,0.005467462,0.0008844016,0.002245074,0.002882473,0.002705174,0.224648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001663924,"about_ca_system_score_gemma":0.00354766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01003032,"about_ca_topic_score_gemma":0.02039272,"domain_scores_codex":[0.9980635,0.0004675543,0.0001854735,0.0007428653,0.0003193038,0.0002212236],"domain_scores_gemma":[0.9910319,0.005319299,0.0004790171,0.001840668,0.0008134193,0.0005156617],"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":[0.00006001976,0.00001774387,0.0004842504,0.0009374408,0.00006874333,0.00001847596,0.00001887102,0.0003009919,0.00005985947,0.0008262502,0.9954879,0.001719515],"study_design_scores_gemma":[0.0008832416,0.000032551,0.001655664,0.0006170494,0.0001290078,0.0001023289,0.00005573263,0.001196066,0.0005658733,0.009531135,0.985171,0.00006020822],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001072318,0.0001124124,0.0003919011,0.0001102866,0.00004418524,0.00002143925,0.995766,0.002268558,0.001177976],"genre_scores_gemma":[0.001555052,0.000194656,0.002176422,0.0002898394,0.00003598299,0.0004503159,0.9912395,0.002142177,0.001915964],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6580648,"threshold_uncertainty_score":0.9386497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02864174708522784,"score_gpt":0.253912330929257,"score_spread":0.2252705838440291,"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."}}