{"id":"W3110931412","doi":"10.26418/bbimst.v8i4.36002","title":"ANALISIS REGRESI LOGISTIK MULTINOMIAL PADA PEMILIHAN ALAT KONTRASEPSI WANITA (Studi Kasus di Puskesmas Sungai Kakap)","year":2019,"lang":"id","type":"article","venue":"Bimaster Buletin Ilmiah Matematika Statistika dan Terapannya","topic":"Healthcare Quality and Satisfaction","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada)","funders":"","keywords":"Physics; Humanities; Gynecology; Medicine; Art","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":[0.03149884,0.001442092,0.002562386,0.001648425,0.00122116,0.003485815,0.001743219,0.00147545,0.02543555],"category_scores_gemma":[0.08916249,0.0008275727,0.008373011,0.002492536,0.001020652,0.004157754,0.001802932,0.005408116,0.004534846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001633479,"about_ca_system_score_gemma":0.00349779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01025968,"about_ca_topic_score_gemma":0.009437663,"domain_scores_codex":[0.9783496,0.01135219,0.002219506,0.003546695,0.00346503,0.001067015],"domain_scores_gemma":[0.8818455,0.09576117,0.008024976,0.005810283,0.007354769,0.001203323],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.009809278,0.001060782,0.671608,0.008845192,0.01420527,0.001449451,0.008301393,0.003458597,0.002004727,0.005925748,0.02357149,0.2497602],"study_design_scores_gemma":[0.0006431604,0.004919311,0.8485934,0.003913267,0.01796656,0.002835161,0.01239994,0.01508318,0.004077439,0.01860607,0.07061145,0.0003510311],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.769886,0.05186522,0.1043682,0.008118497,0.002342463,0.003782317,0.02082041,0.001145822,0.03767109],"genre_scores_gemma":[0.9455148,0.005198543,0.01568343,0.001470778,0.0003605965,0.002838362,0.003649218,0.0004015378,0.02488279],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03149884,"threshold_uncertainty_score":0.1665838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05940762449310714,"score_gpt":0.3671330767734496,"score_spread":0.3077254522803425,"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."}}