{"id":"W2159989659","doi":"10.1017/s0266462304001102","title":"Using decision modeling to determine pricing of new pharmaceuticals: The case of neurokinin-1 receptor antagonist antiemetics for cancer chemotherapy","year":2004,"lang":"en","type":"article","venue":"International Journal of Technology Assessment in Health Care","topic":"Nausea and vomiting management","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency; Cancer Care Ontario","funders":"","keywords":"Medicine; Antiemetic; Context (archaeology); Aprepitant; Vomiting; Quality-adjusted life year; Granisetron; Intensive care medicine; Cost effectiveness; Emergency medicine; Anesthesia","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":[],"consensus_categories":[],"category_scores_codex":[0.0004897582,0.00009302545,0.0003277575,0.0005901503,0.00004293292,0.000008044318,0.0002428665,0.00006276403,0.000009240916],"category_scores_gemma":[0.0001751521,0.00007090864,0.00008432307,0.0002498572,0.00003708916,0.00004520483,0.00006583142,0.0002729044,7.047218e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005926361,"about_ca_system_score_gemma":0.0006674091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002429455,"about_ca_topic_score_gemma":0.00003949895,"domain_scores_codex":[0.998546,0.00001988267,0.0008829309,0.0001213064,0.0002742976,0.0001555755],"domain_scores_gemma":[0.9984971,0.00009784482,0.0005572487,0.0001264456,0.0006570623,0.00006426729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002940899,0.0007172551,0.03370797,0.0009185845,0.000595599,0.0006693844,0.002425913,0.1114697,0.04122744,0.004389625,0.0002149494,0.8007227],"study_design_scores_gemma":[0.1056142,0.01937112,0.008797594,0.04102823,0.001304633,0.01417726,0.06935079,0.2871768,0.4048444,0.01591171,0.03086325,0.001560116],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8668355,0.0007241487,0.1052476,0.02613806,0.0005941913,0.0004337644,0.0000132957,0.000007174814,0.000006218818],"genre_scores_gemma":[0.8849667,0.0006370069,0.1133838,0.0008730903,0.0001182124,0.000004327098,0.000001407011,0.0000132781,0.000002209576],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7991626,"threshold_uncertainty_score":0.289157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.104559850029071,"score_gpt":0.5088328298373925,"score_spread":0.4042729798083215,"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."}}