{"id":"W2522066320","doi":"10.2298/fil1705395c","title":"The transmuted generalized modified Weibull distribution","year":2017,"lang":"en","type":"article","venue":"Filomat","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Higher Education Commision, Pakistan; Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Weibull distribution; Mathematics; Statistics; Applied mathematics; Goodness of fit; Exponentiated Weibull distribution; Statistic; Order statistic; Hazard; Statistical physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0001947498,0.0001024819,0.0001176686,0.000006831831,0.001742527,0.0002513915,0.0003628197,0.00005640107,0.0002639047],"category_scores_gemma":[0.001076689,0.00007099699,0.00006713762,0.00004111247,0.0001773206,0.00008094338,0.00003431169,0.00008419293,0.0001898077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003825461,"about_ca_system_score_gemma":0.000020807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000162422,"about_ca_topic_score_gemma":0.00001285823,"domain_scores_codex":[0.9991842,0.00003931396,0.0002455686,0.0001502654,0.0001839313,0.0001967028],"domain_scores_gemma":[0.9986414,0.0003215457,0.0001599713,0.0006928634,0.0001020823,0.00008207682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001174904,0.00003579652,0.00001149582,0.000007513449,0.00001182214,7.673014e-7,0.00001561805,0.000002243103,0.0001402464,0.9586184,0.03818882,0.002955537],"study_design_scores_gemma":[0.001056901,0.0000176853,0.02385612,0.00001723794,0.00005796743,0.000007937231,0.00002330612,0.03291177,0.001504548,0.8525542,0.08776402,0.0002283128],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02291373,0.00001597219,0.9553599,0.008642212,0.000177913,0.0004028055,0.001356821,0.0002040132,0.01092664],"genre_scores_gemma":[0.9946427,0.00001712789,0.003176362,0.00005806146,0.00006117481,0.0001448269,0.0004337587,0.00001163506,0.001454314],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.971729,"threshold_uncertainty_score":0.9995571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1019792926731346,"score_gpt":0.3867994310274394,"score_spread":0.2848201383543048,"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."}}