{"id":"W2973433556","doi":"10.1097/01.npr.0000580796.97474.91","title":"Medicare for all?","year":2019,"lang":"en","type":"article","venue":"The Nurse Practitioner","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"State (computer science); Gerontology; Genealogy; Family medicine; Medicine; Library science; Sociology; History; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001043274,0.0001794472,0.0002825174,0.0005330365,0.001693941,0.001275546,0.0005105162,0.002248351,0.1701813],"category_scores_gemma":[0.009223722,0.0001233094,0.0003312493,0.0006421675,0.0003763258,0.001966263,0.001574317,0.002091426,0.02776094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001205946,"about_ca_system_score_gemma":0.003558748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01275295,"about_ca_topic_score_gemma":0.02359386,"domain_scores_codex":[0.9992775,0.0001636563,0.0000338338,0.00006307174,0.0002548223,0.0002070695],"domain_scores_gemma":[0.9969454,0.0002966052,0.0002123144,0.00008822074,0.000380858,0.002076563],"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":[0.00000898988,0.00001398686,0.001026279,0.00002055486,0.000002700379,0.00003276788,0.00004754418,0.00000459783,0.00001240113,0.001913134,0.9648035,0.03211373],"study_design_scores_gemma":[0.00001905106,0.00002220427,0.008303438,0.0002506928,0.000006157623,0.0002465326,0.0003568216,0.00002246048,0.0000338071,0.001696783,0.9890354,0.00000661402],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.003201826,0.007850188,0.0001136925,0.7896773,0.009368978,0.00004370971,0.002017176,0.0001115428,0.1876156],"genre_scores_gemma":[0.05981045,0.0203645,0.0007971927,0.6128729,0.01314405,0.0001893109,0.0040465,0.0001737547,0.2886014],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.1701813,"threshold_uncertainty_score":0.5693133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05710482183786779,"score_gpt":0.4592629263842691,"score_spread":0.4021581045464013,"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."}}