{"id":"W2954946792","doi":"10.1016/j.jval.2019.04.184","title":"PCN60 FITTING DISTRIBUTIONS OF PARAMETRIC MODELS INTO NON-PARAMETRIC KAPLAN-MEIER CURVE: APPLICATION IN EXCEL AND COMPARISON OF DIFFERENT DATA RECREATION METHODS","year":2019,"lang":"en","type":"article","venue":"Value in Health","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Cancer Care Ontario","funders":"","keywords":"Weibull distribution; Parametric statistics; Statistics; Goodness of fit; Mathematics; Distribution fitting; Parametric model; Survival analysis; Computer science; Exponential distribution","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":[],"consensus_categories":[],"category_scores_codex":[0.01093546,0.001094562,0.0009631398,0.003260177,0.00049653,0.001868579,0.001637383,0.0008428362,0.01733845],"category_scores_gemma":[0.05953311,0.0006887413,0.001282873,0.002382301,0.0003724374,0.002034656,0.001757643,0.001534919,0.003265833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007009386,"about_ca_system_score_gemma":0.001847992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004517888,"about_ca_topic_score_gemma":0.002893605,"domain_scores_codex":[0.9962292,0.00190665,0.0004505513,0.0005033017,0.0007358672,0.0001743847],"domain_scores_gemma":[0.9636787,0.02924168,0.001361631,0.002820176,0.002694521,0.0002033546],"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":[0.001374402,0.0008661541,0.02427893,0.001219043,0.0004733555,0.0004790545,0.001682194,0.1620291,0.004212989,0.04031749,0.03108823,0.7319791],"study_design_scores_gemma":[0.0001235451,0.0002831042,0.0100724,0.000202656,0.0000865972,0.000546706,0.0003752082,0.9387031,0.00928312,0.01961335,0.02057154,0.0001386411],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03362307,0.0001396804,0.9443973,0.0001174748,0.00006757636,0.0003965314,0.002691343,0.01533806,0.003228874],"genre_scores_gemma":[0.2377961,0.000345063,0.7433887,0.00008476956,0.00004086814,0.001824381,0.005100338,0.006755509,0.004664285],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01733845,"threshold_uncertainty_score":0.05800289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4980769727827197,"score_gpt":0.5119474165045507,"score_spread":0.01387044372183094,"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."}}