{"id":"W2622573342","doi":"10.1177/0840470417696709","title":"Innovation, productivity, and pricing: Capturing value from precision medicine technology in Canada","year":2017,"lang":"en","type":"article","venue":"Healthcare Management Forum","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of New Brunswick","funders":"","keywords":"Productivity; Reimbursement; Value (mathematics); Sustainability; Precision medicine; Health technology; Economics; Paradigm shift; Technological change; Industrial organization; Business; Marketing; Health care; Medicine; Economic growth; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003816172,0.0005881671,0.0008447514,0.004753052,0.003381933,0.006251992,0.00185005,0.001218804,0.002681398],"category_scores_gemma":[0.02814717,0.0003594281,0.0009432336,0.01490881,0.002026718,0.002052833,0.002398554,0.002164086,0.0002026986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.13462,"about_ca_system_score_gemma":0.1442003,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9978434,"about_ca_topic_score_gemma":0.9966739,"domain_scores_codex":[0.9970344,0.0005025541,0.0001251493,0.0002416661,0.001197626,0.000898642],"domain_scores_gemma":[0.9867694,0.004363811,0.001382116,0.0003927937,0.005228811,0.001862993],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004086616,0.0003001362,0.6557133,0.0002533349,0.0005187027,0.0004716573,0.00240445,0.09399787,0.000199188,0.1110013,0.03581345,0.09891805],"study_design_scores_gemma":[0.0001481157,0.00009163147,0.5512072,0.0005025427,0.0004483298,0.0001528664,0.006187355,0.3421405,0.0004294449,0.05884688,0.03955156,0.0002934968],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.901677,0.01011374,0.01073966,0.02737361,0.0002125073,0.0002575126,0.00943423,0.0001598816,0.04003186],"genre_scores_gemma":[0.9890378,0.002285087,0.003000168,0.0003500196,0.00003929305,0.00003367329,0.001886075,0.00002661278,0.003341356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.13462,"threshold_uncertainty_score":0.9767413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04591102958574244,"score_gpt":0.2800940398590283,"score_spread":0.2341830102732859,"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."}}