{"id":"W4287755157","doi":"10.48550/arxiv.2006.10833","title":"","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada; Canadian Institute for Advanced Research","keywords":"Causal model; Computer science; Causal structure; Series (stratigraphy); Causal analysis; Graph; Theoretical computer science; Confounding; Machine learning; Artificial intelligence; Data mining; Mathematics; Econometrics; Statistics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01056617,0.001230042,0.001735004,0.002953075,0.001197431,0.002479441,0.003835354,0.002677651,0.007838786],"category_scores_gemma":[0.04620336,0.001116078,0.002730986,0.003242086,0.002232583,0.005959617,0.002215011,0.004337181,0.002187267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0017991,"about_ca_system_score_gemma":0.001982786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009785641,"about_ca_topic_score_gemma":0.01368643,"domain_scores_codex":[0.9948789,0.002532149,0.0002027366,0.001684354,0.0005509697,0.0001509401],"domain_scores_gemma":[0.9680962,0.02508202,0.001608296,0.00400942,0.0008217186,0.0003823158],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002893832,0.0003387774,0.01897443,0.0007571562,0.001103196,0.0004389609,0.0004331766,0.2629915,0.00177606,0.4068339,0.01822636,0.2878371],"study_design_scores_gemma":[0.00003121624,0.00004290621,0.001845,0.00009889338,0.00008102076,0.0001576146,0.00006086361,0.6088116,0.0005763767,0.3812388,0.007022607,0.00003312311],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.009395195,0.0008227347,0.9842936,0.001810906,0.000101395,0.000101661,0.001041021,0.0005529388,0.001880543],"genre_scores_gemma":[0.3795678,0.002377154,0.6022319,0.001612129,0.00066702,0.0006491654,0.004941485,0.0003443531,0.007609044],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9921612,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1539157096516495,"score_gpt":0.1936386869331215,"score_spread":0.03972297728147198,"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."}}