{"id":"W4398918028","doi":"10.7910/dvn/zbrtjh/bclvgk","title":"Table2Sim5kLoadModules.R","year":2019,"lang":"sr","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); Computer science; Artificial intelligence; Statistics; Mathematics; 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","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009833358,0.001151528,0.001172898,0.0004080971,0.0003779963,0.001460657,0.00684774,0.0009751164,0.02894022],"category_scores_gemma":[0.0002592565,0.001191555,0.0003600983,0.0007355509,0.000260129,0.00178178,0.003655689,0.001707467,0.8195061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002366285,"about_ca_system_score_gemma":0.001103534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004440696,"about_ca_topic_score_gemma":0.00004869626,"domain_scores_codex":[0.9933055,0.0003546893,0.001039611,0.002495368,0.001297736,0.001507078],"domain_scores_gemma":[0.9907439,0.0002273983,0.0006465915,0.007417093,0.0003441278,0.0006208629],"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":[0.00003267095,0.0002393895,0.000008410118,0.0003290574,0.0001333683,0.00020821,0.00007833581,0.0003949354,0.00003164089,0.002576548,0.9909938,0.004973621],"study_design_scores_gemma":[0.0007020945,0.0002118885,0.0000185359,0.0005509167,0.0001791924,0.00007970438,0.00003328225,0.04485333,0.00006413112,0.0003517547,0.9516101,0.001345039],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001394741,0.00001181091,0.1816733,0.00003320281,0.004532228,0.0004829136,0.8121769,0.0001560153,0.000919615],"genre_scores_gemma":[0.0004257094,0.001239164,0.00670435,0.001907409,0.00072664,0.00003290726,0.9840576,0.00006902453,0.0048372],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7905659,"threshold_uncertainty_score":0.9995759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03533664793010745,"score_gpt":0.2616550964063201,"score_spread":0.2263184484762127,"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."}}