{"id":"W2995883695","doi":"10.1016/j.jval.2019.09.633","title":"PCN440 NETWORK META-ANALYSIS USING FRACTIONAL POLYNOMIALS: HEURISTIC FOR MODEL SELECTION INCORPORATING BEYOND-TRIAL EXTRAPOLATIONS (A MELANOMA EXAMPLE)","year":2019,"lang":"en","type":"article","venue":"Value in Health","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Precision Nanosystems (Canada)","funders":"","keywords":"Model selection; Gompertz function; Weibull distribution; Mathematics; Extrapolation; Deviance (statistics); Boolean model; Statistics; Parametric statistics; Computer science; Econometrics","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":[0.01915559,0.001238575,0.002934251,0.002376669,0.001244796,0.001423206,0.001987549,0.001605934,0.005105698],"category_scores_gemma":[0.06189375,0.0006923381,0.003112914,0.002617473,0.0007030506,0.00150202,0.001600832,0.003405678,0.0003916499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001288009,"about_ca_system_score_gemma":0.003155655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01735487,"about_ca_topic_score_gemma":0.02274297,"domain_scores_codex":[0.9923612,0.006729954,0.0001452513,0.000337394,0.0003021398,0.0001239932],"domain_scores_gemma":[0.9632805,0.03369435,0.0005140849,0.001297511,0.000933674,0.0002797701],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001231161,0.0001783401,0.002965429,0.0007095667,0.002087351,0.00036942,0.000210064,0.8410246,0.0004161767,0.03428943,0.006121916,0.1103965],"study_design_scores_gemma":[0.0002337173,0.000124121,0.0003119021,0.00009231845,0.0004288159,0.00006276101,0.00002970807,0.9441207,0.0001698634,0.05283741,0.001564988,0.00002369695],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02200611,0.002664599,0.9703241,0.001614541,0.0001377913,0.0002215756,0.0004969736,0.0004791979,0.002055206],"genre_scores_gemma":[0.323561,0.001228587,0.6711383,0.0005839121,0.0001601878,0.0005346266,0.0004582925,0.0002431386,0.002092006],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01915559,"threshold_uncertainty_score":0.1013057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.796887340975208,"score_gpt":0.5686788188507079,"score_spread":0.2282085221245,"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."}}