{"id":"W2922591312","doi":"10.7202/1060028ar","title":"Access to Medical Technologies: Do Gender and Social Capital matter?","year":2019,"lang":"en","type":"article","venue":"Management international","topic":"Global Health Care Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"Université de Montpellier; Agence Nationale de la Recherche","keywords":"Social capital; Context (archaeology); German; Interpersonal ties; Business; Demographic economics; Capital (architecture); Sample (material); Public relations; Psychology; Political science; Sociology; Social psychology; Economics; Social science; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001553905,0.0002032416,0.000322151,0.001022765,0.0008606784,0.00154621,0.0003888071,0.0005567736,0.006795147],"category_scores_gemma":[0.01009783,0.0001294273,0.000265521,0.001195039,0.001224744,0.001394262,0.001226582,0.000553617,0.0003454206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006784936,"about_ca_system_score_gemma":0.0007193842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006476419,"about_ca_topic_score_gemma":0.01042077,"domain_scores_codex":[0.9986923,0.0004578335,0.00007062511,0.0001507093,0.0002434336,0.0003850388],"domain_scores_gemma":[0.9862482,0.006191147,0.005171472,0.0003529115,0.0002858153,0.001750491],"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":[0.0001048168,0.0001490099,0.986285,0.00003204161,0.00006025163,0.000147101,0.003301932,0.00006199905,0.0001260865,0.0009734361,0.0002103342,0.008548011],"study_design_scores_gemma":[0.000006968824,0.0001294162,0.9910004,0.00003237649,0.00002630115,0.0001273916,0.006756993,0.0002133881,0.00006139819,0.0006389813,0.0009988456,0.000007574094],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996411,0.000296579,0.0001211515,0.0003695901,0.000008726974,0.000009195325,0.0001242127,0.00000113061,0.002658496],"genre_scores_gemma":[0.999566,0.00006569902,0.0000332834,0.00002929247,0.000006337599,0.000003519193,0.00002716755,5.71318e-7,0.0002681626],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006795147,"threshold_uncertainty_score":0.02273202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05521072278411456,"score_gpt":0.4609254188328763,"score_spread":0.4057146960487618,"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."}}