{"id":"W3203362329","doi":"10.1080/08982112.2021.1938118","title":"Identifying dominant causes using leveraged study designs","year":2021,"lang":"en","type":"article","venue":"Quality Engineering","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Exploit; Computer science; Process (computing); Plan (archaeology); Variation (astronomy); Data mining; Computer security","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.3574996,0.00235284,0.00415763,0.009013603,0.002407294,0.003578311,0.003407935,0.003802408,0.004787507],"category_scores_gemma":[0.5026447,0.001125672,0.00654917,0.003710072,0.005213467,0.005299574,0.006139116,0.003663409,0.0003761945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002427095,"about_ca_system_score_gemma":0.006149135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007929154,"about_ca_topic_score_gemma":0.001042851,"domain_scores_codex":[0.518294,0.4005287,0.02357732,0.02415875,0.03163648,0.001804651],"domain_scores_gemma":[0.3010893,0.6038108,0.02854003,0.04906778,0.01629943,0.001192599],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00787999,0.001338984,0.08157867,0.008440337,0.02136617,0.001168548,0.007204324,0.03085582,0.01024727,0.2800468,0.003031261,0.5468419],"study_design_scores_gemma":[0.005308162,0.01437298,0.0314695,0.00241428,0.01147299,0.001015154,0.002076128,0.2582075,0.02347208,0.6333832,0.01621178,0.0005962737],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02849947,0.0008690963,0.9635451,0.0005813596,0.0001871116,0.00464504,0.000180805,0.0002123091,0.001279737],"genre_scores_gemma":[0.4052761,0.0002877471,0.584294,0.0003662338,0.0001208406,0.009105793,0.0001210475,0.00005227028,0.0003760292],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3574996,"threshold_uncertainty_score":0.7923174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5503989095260722,"score_gpt":0.5362244254218561,"score_spread":0.01417448410421607,"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."}}