{"id":"W4401754044","doi":"10.1109/ichi61247.2024.00073","title":"A Topological Data Analysis of Un met Health Care Needs Among Injured Patients","year":2024,"lang":"en","type":"article","venue":"","topic":"Topological and Geometric Data Analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Topological data analysis; Health care; Computer science; Topology (electrical circuits); Business; Medicine; Political science; Mathematics; Combinatorics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003958528,0.0001328163,0.0005000011,0.001442547,0.00007317012,0.0001421491,0.002133801,0.000070728,0.0005856664],"category_scores_gemma":[0.0001518509,0.00008271232,0.0001994772,0.01404635,0.00009174841,0.0004764461,0.001632288,0.0001196698,0.00002120549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003613483,"about_ca_system_score_gemma":0.00004852994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001104959,"about_ca_topic_score_gemma":0.0001693545,"domain_scores_codex":[0.9981337,0.0001279525,0.0004330532,0.000617646,0.0004155217,0.00027208],"domain_scores_gemma":[0.9980427,0.000181761,0.00008856554,0.001450268,0.000085333,0.0001513433],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000007296331,0.0003456249,0.1165878,0.00005201622,0.00332132,0.00001809726,0.001649499,0.0001288779,0.000002010848,0.1497748,0.00651102,0.7216016],"study_design_scores_gemma":[0.0004930086,0.001389565,0.8108854,0.00002650513,0.002355729,0.00000123494,0.001462806,0.154818,0.0001107726,0.004407523,0.02328465,0.0007647141],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2867056,0.003994315,0.6995259,0.003241405,0.0004794056,0.0002865221,0.001542436,0.0006141833,0.00361028],"genre_scores_gemma":[0.9837531,0.00005160534,0.01475638,0.000410329,0.0000159489,0.000002970252,0.000853197,0.000002608225,0.0001538828],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7208369,"threshold_uncertainty_score":0.6748807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02814135079369484,"score_gpt":0.3056940308985888,"score_spread":0.277552680104894,"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."}}