{"id":"W2000599038","doi":"10.1017/s0266462306050781","title":"Framework for describing and classifying decision-making systems using technology assessment to determine the reimbursement of health technologies (fourth hurdle systems)","year":2006,"lang":"en","type":"review","venue":"International Journal of Technology Assessment in Health Care","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":102,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reimbursement; Health technology; Management science; Technology assessment; Clinical decision making; Healthcare system; Computer science; Operations research; Data science; Actuarial science; Medicine; Business; Health care; Family medicine; Engineering; Economics; Political science; Economic growth","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.01764386,0.000541484,0.00467942,0.005949004,0.0003769517,0.0001835075,0.00185307,0.001000771,0.000004300179],"category_scores_gemma":[0.003759278,0.0005063711,0.0003472331,0.001003119,0.0002050949,0.0002631207,0.0005225478,0.001665843,0.00000269491],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008730949,"about_ca_system_score_gemma":0.002596541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002833433,"about_ca_topic_score_gemma":0.00006155694,"domain_scores_codex":[0.9842669,0.0005830044,0.01310043,0.0008075472,0.0004701969,0.000771885],"domain_scores_gemma":[0.9760457,0.002966725,0.01939058,0.0007980737,0.0007137478,0.00008517253],"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":[0.00001912207,0.0001805058,0.005253681,0.02158391,0.0006317492,0.00001968587,0.0003276296,0.004246047,2.309188e-7,0.3359733,0.0006754867,0.6310887],"study_design_scores_gemma":[0.00149166,0.001470573,0.0002364119,0.2160568,0.0001406158,0.0009104592,0.05340174,0.008997049,5.062676e-7,0.02593319,0.6902596,0.001101377],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0006199392,0.7700054,0.1992769,0.02373042,0.002855209,0.003063406,0.0003645172,0.00006926613,0.00001491913],"genre_scores_gemma":[0.08607469,0.6776832,0.234436,0.0005891386,0.0003262671,0.0007168489,0.00004006579,0.0001276382,0.000006224614],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.6895841,"threshold_uncertainty_score":0.9997388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4411013407123863,"score_gpt":0.566950204178412,"score_spread":0.1258488634660257,"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."}}