{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003286405,0.0004175328,0.0004445309,0.0001982662,0.0001062408,0.0004731048,0.004020219,0.0003838043,0.004683329],"category_scores_gemma":[0.0000849869,0.0004049197,0.0001274217,0.000283331,0.00005568561,0.0007924657,0.001588461,0.0006516271,0.415052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007764456,"about_ca_system_score_gemma":0.0003495113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001676222,"about_ca_topic_score_gemma":0.00001917443,"domain_scores_codex":[0.9974911,0.00009128961,0.0003578595,0.0009830948,0.000536073,0.0005405917],"domain_scores_gemma":[0.9953815,0.00007261034,0.0002129932,0.004025702,0.0001057371,0.0002014665],"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":[0.000003505596,0.00004688835,5.757051e-7,0.00007443626,0.00002893758,0.00005340246,0.000007621565,0.00006267137,0.000004837005,0.001017239,0.997754,0.0009459328],"study_design_scores_gemma":[0.0002080247,0.00004768998,0.000002699928,0.00009820115,0.00003198454,0.00002415506,0.000002885084,0.006694329,0.0000158838,0.000348286,0.9920282,0.0004976889],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[5.736325e-7,0.000002964857,0.131797,0.00001264134,0.001582647,0.0001625682,0.8659977,0.0001239253,0.0003200697],"genre_scores_gemma":[0.00001032503,0.0002711049,0.00572821,0.0009639966,0.0001961016,0.00001627042,0.9919581,0.00001616733,0.0008397084],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4103687,"threshold_uncertainty_score":0.9998403,"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."}}