{"id":"W4398952834","doi":"10.7910/dvn/zbrtjh/ylvh8c","title":"Table2Sim1kLoadModules.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; Mathematics; Statistics; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003239512,0.0004147853,0.0004401675,0.0001922678,0.0001089562,0.0004862855,0.004001104,0.0003810459,0.004796465],"category_scores_gemma":[0.00008175938,0.000402914,0.0001283212,0.0002739814,0.00005667101,0.0007810651,0.00158474,0.0006439301,0.4207256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007490999,"about_ca_system_score_gemma":0.0003500095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001566727,"about_ca_topic_score_gemma":0.0000184835,"domain_scores_codex":[0.9975122,0.00008989855,0.0003548004,0.0009753733,0.0005316469,0.0005360324],"domain_scores_gemma":[0.9954306,0.00007193232,0.0002118952,0.003982607,0.0001032249,0.0001996714],"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":[0.000003476233,0.00004785035,5.164661e-7,0.00007350805,0.00002889623,0.00005414039,0.000007625604,0.00005911606,0.00000533692,0.001066626,0.9974736,0.001179298],"study_design_scores_gemma":[0.0002082303,0.00004853563,0.000002334639,0.00009517539,0.00003214924,0.00002488407,0.000002982908,0.006317696,0.00001858755,0.0003538558,0.9924002,0.0004954274],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[5.499055e-7,0.000002782519,0.1343669,0.00001267239,0.001547332,0.000160864,0.8634593,0.0001216888,0.0003279424],"genre_scores_gemma":[0.00001030322,0.0001931298,0.005946086,0.0009646516,0.000190148,0.00001630111,0.9918568,0.00001602245,0.0008065952],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4159291,"threshold_uncertainty_score":0.9998423,"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."}}