{"id":"W4384008685","doi":"10.1371/journal.pone.0286593","title":"A new trigonometric modification of the Weibull distribution: Control chart and applications in quality control","year":2023,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Weibull distribution; Estimator; Control chart; Statistics; Trigonometry; Chart; Computer science; Weibull modulus; Mathematics; Algorithm; Reliability engineering; Applied mathematics; Engineering; Process (computing)","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":[],"consensus_categories":[],"category_scores_codex":[0.000398508,0.00009745608,0.0002740745,0.00008659062,0.0001099615,0.00001885646,0.000156082,0.00006272074,0.00007651382],"category_scores_gemma":[0.001669626,0.00007999311,0.00004639336,0.001448365,0.00008367949,0.000048505,0.00002375526,0.0001100721,0.00004471606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005957698,"about_ca_system_score_gemma":0.00005578082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002978822,"about_ca_topic_score_gemma":0.000007887206,"domain_scores_codex":[0.9987696,0.00009669163,0.0005043242,0.000196442,0.0002777813,0.000155145],"domain_scores_gemma":[0.9978216,0.00137135,0.0002165247,0.0003594029,0.0001423019,0.00008878425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00001729769,0.000636783,0.006177207,0.0001128425,0.0000464862,4.925453e-8,0.00005085073,0.00001067842,0.001349803,0.9895569,0.001170912,0.0008701996],"study_design_scores_gemma":[0.003098944,0.00002905871,0.7579047,0.00008102209,0.000228717,4.641349e-7,0.0001461657,0.02001736,0.001702047,0.2159542,0.0006231774,0.000214133],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08890207,0.00005087424,0.9004371,0.005630758,0.00001297772,0.001845232,0.002620663,0.0001337225,0.000366623],"genre_scores_gemma":[0.9980381,0.00001707683,0.0008232621,0.000044808,0.00003147169,0.0004988064,0.0002281476,0.000008256307,0.0003101413],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9091359,"threshold_uncertainty_score":0.3262024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1554904686239652,"score_gpt":0.3513450503369192,"score_spread":0.1958545817129539,"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."}}