{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002923678,0.0002009961,0.0004413129,0.000154675,0.0002342431,0.0003785531,0.0003885852,0.00005132931,0.00009249234],"category_scores_gemma":[0.01512942,0.0001880573,0.00008425347,0.0009274041,0.00002588869,0.000535396,0.0002462793,0.0002726226,0.00004616568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001437181,"about_ca_system_score_gemma":0.00008292589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000536438,"about_ca_topic_score_gemma":0.00002520136,"domain_scores_codex":[0.9963962,0.0003033702,0.0009213306,0.0006342338,0.001339023,0.0004058583],"domain_scores_gemma":[0.9959919,0.002696911,0.0001558296,0.0006217702,0.0003741522,0.0001594316],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005027585,0.0005359065,0.04959928,0.0001834212,0.0001671018,0.001340475,0.009035612,0.3984658,0.516968,0.006557021,0.00005207765,0.0170451],"study_design_scores_gemma":[0.004291525,0.0002263635,0.301723,0.0005178859,0.0002408738,0.0001909317,0.06150699,0.2287594,0.3481818,0.04887302,0.001881126,0.003607014],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4382032,0.0001223216,0.5609428,0.00001168301,0.0005446888,0.00008351974,0.000005118091,0.00005442951,0.00003215713],"genre_scores_gemma":[0.9434733,0.000002224732,0.05612384,0.00001394442,0.0001461686,0.000009127839,9.738136e-7,0.00002613808,0.0002042811],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5052701,"threshold_uncertainty_score":0.9931666,"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."}}