{"id":"W4396616886","doi":"10.3390/curroncol31050184","title":"New Anticancer Drugs: Reliably Assessing “Value” While Addressing High Prices","year":2024,"lang":"en","type":"article","venue":"Current Oncology","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Essar Steel Algoma (Canada); Ottawa Hospital; University Health Network; University of Toronto; Jewish General Hospital; St. Michael's Hospital; Arthur B. McDonald-Canadian Astroparticle Physics Research Institute; Princess Margaret Cancer Centre; University of Calgary; McGill University; University of Ottawa; Wilfrid Laurier University","funders":"AstraZeneca; Amgen","keywords":"Medicine; Drug development; Value (mathematics); Cost–benefit analysis; Actuarial science; Disease; Drug prices; Public economics; Drug; Business; Pharmacology; Economics; Political science; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.02282121,0.0006877787,0.0008747315,0.003525877,0.0003446948,0.003932494,0.0007047773,0.001187023,0.003040667],"category_scores_gemma":[0.1233152,0.0002543739,0.0005048994,0.005749718,0.001546183,0.004002502,0.001477422,0.001845655,0.0007741812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005104514,"about_ca_system_score_gemma":0.003926141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02698274,"about_ca_topic_score_gemma":0.02282252,"domain_scores_codex":[0.9807218,0.01359836,0.00103343,0.0006488269,0.003676284,0.0003213342],"domain_scores_gemma":[0.9324485,0.04799213,0.008173882,0.002634922,0.008251798,0.0004987189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005886598,0.0001902425,0.1669527,0.001780133,0.0008646577,0.0002126242,0.0005144874,0.06382857,0.0003923729,0.1789526,0.05182105,0.5339018],"study_design_scores_gemma":[0.0001560684,0.0005418415,0.1924025,0.002749091,0.0005567785,0.0005006538,0.002261481,0.2097791,0.003030143,0.4797185,0.1080489,0.0002548272],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2437951,0.06178068,0.2881549,0.07835967,0.001195998,0.002242314,0.01990263,0.0006404658,0.3039283],"genre_scores_gemma":[0.9198707,0.00956988,0.06069693,0.00205037,0.0003381859,0.0004544457,0.002478034,0.0000858623,0.004455573],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02698274,"threshold_uncertainty_score":0.1206915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6285406275088642,"score_gpt":0.5598705806997936,"score_spread":0.06867004680907063,"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."}}