{"id":"W3122334677","doi":"","title":"Breaking Gridlock in Health Policy? Comment on 'A New Synthesis","year":2014,"lang":"en","type":"article","venue":"Research Information System of Ardabil University of Medical Sciences (Ardabil University of Medical Sciences)","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Medical Association","funders":"","keywords":"Gridlock; Health care; Inequality; Investment (military); Population health; Population; Resource (disambiguation); Economics; Public economics; Business; Economic growth; Political science; Medicine; Computer science; Law","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":[0.03428737,0.00123524,0.002057897,0.002268749,0.00472889,0.01034738,0.008457663,0.04069556,0.02416065],"category_scores_gemma":[0.1366793,0.0009629531,0.003218446,0.004062492,0.01138242,0.02616931,0.006140355,0.05257854,0.00587395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01209499,"about_ca_system_score_gemma":0.0166354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04889026,"about_ca_topic_score_gemma":0.04432289,"domain_scores_codex":[0.9813017,0.007183855,0.001198558,0.003441246,0.004578579,0.002296116],"domain_scores_gemma":[0.8674273,0.1123186,0.003818812,0.003432222,0.01023897,0.002764129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006188174,0.000009752764,0.0002068982,0.0003198722,0.00002427728,0.0000770135,0.0003486777,0.0001742297,0.00002535094,0.03004675,0.9641961,0.004509205],"study_design_scores_gemma":[0.0002020353,0.0000425635,0.00200059,0.002799815,0.00008986535,0.0001478577,0.002104483,0.0005628534,0.0002504744,0.08423172,0.9074258,0.0001419044],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.00007996826,0.002048382,0.00009047111,0.9909472,0.005837356,0.000004411177,0.0001167866,0.00001531144,0.0008601413],"genre_scores_gemma":[0.003742009,0.001840494,0.0001801046,0.9784828,0.01435233,0.00004344525,0.00004742796,0.00002695021,0.00128452],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.04889026,"threshold_uncertainty_score":0.1813312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1412494838368276,"score_gpt":0.3419364933866178,"score_spread":0.2006870095497902,"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."}}