{"id":"W4380987419","doi":"10.1016/j.heliyon.2023.e17238","title":"A new modification of the flexible Weibull distribution based on power transformation: Monte Carlo simulation and applications","year":2023,"lang":"en","type":"article","venue":"Heliyon","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Deanship of Scientific Research, King Saud University; King Faisal University","keywords":"Weibull distribution; Estimator; Computer science; Failure rate; Transformation (genetics); Power (physics); Reliability engineering; Data mining; Statistics; Mathematics; Engineering","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":[0.0001795997,0.0001161763,0.0001282283,0.00006304805,0.00021775,0.00002837683,0.0001156848,0.00007915287,0.00008390964],"category_scores_gemma":[0.0002322998,0.00009486017,0.00006248472,0.0007496966,0.00005751966,0.00008482113,0.00001529466,0.00009543714,0.00007094716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005932981,"about_ca_system_score_gemma":0.00005863945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006502009,"about_ca_topic_score_gemma":0.000003104046,"domain_scores_codex":[0.9989543,0.00004844855,0.0003659329,0.0001846667,0.0003070355,0.0001396066],"domain_scores_gemma":[0.9988477,0.0004033623,0.0001539325,0.0003631577,0.0001521306,0.00007971196],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003308936,0.0001191414,0.000110163,0.0002427553,0.00001002948,7.569265e-8,0.0002513296,0.05228968,0.0002772292,0.9375646,0.00266701,0.006434958],"study_design_scores_gemma":[0.001038212,0.00007177066,0.04471275,0.0002186728,0.00008276162,0.000001298586,0.0001753262,0.8744442,0.002418897,0.04708472,0.0294856,0.0002658264],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007628794,0.00002315154,0.9871143,0.002241147,0.00004366603,0.0009017115,0.0006763893,0.0002092669,0.001161548],"genre_scores_gemma":[0.9979659,0.00001560582,0.001119459,0.00008336532,0.00002385306,0.0002018178,0.0002241866,0.00001261055,0.0003531862],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9903371,"threshold_uncertainty_score":0.3868286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06815154767271314,"score_gpt":0.3618238920470396,"score_spread":0.2936723443743265,"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."}}