{"id":"W4366507037","doi":"10.1109/icomet57998.2023.10099343","title":"Visualizing Research on Explainable Artificial Intelligence for Medical and Healthcare","year":2023,"lang":"en","type":"article","venue":"","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pace; Field (mathematics); Computer science; Data science; Health care; Artificial intelligence; China; Thematic map; Knowledge management; Political science; Geography; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005279854,0.00009961938,0.0001444572,0.0003885256,0.0006093904,0.0001736063,0.0007042783,0.00012367,0.00003617863],"category_scores_gemma":[0.002016181,0.00008763024,0.00002866208,0.001183652,0.00007647119,0.000137643,0.0004820184,0.0005161207,0.0001635601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006138909,"about_ca_system_score_gemma":0.0002457536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005699731,"about_ca_topic_score_gemma":0.0002004747,"domain_scores_codex":[0.9971139,0.0003742788,0.0003023806,0.0005727751,0.0009386961,0.0006979649],"domain_scores_gemma":[0.9966295,0.002365818,0.00003203165,0.0004166966,0.0002304852,0.000325437],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001121213,0.00001372886,0.0002019372,0.0001847761,0.000001721089,0.00002706814,0.000761965,0.00005528704,0.000007089079,0.789651,0.001266508,0.2078177],"study_design_scores_gemma":[0.00006361555,0.0007822269,0.0005363051,0.0001878305,4.816959e-7,0.00001656342,0.001328622,0.8543963,0.0007668202,0.1325105,0.009238369,0.0001723417],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04866527,0.0002337488,0.6900673,0.2546401,0.0009472237,0.001364636,0.000004247182,0.001536614,0.002540865],"genre_scores_gemma":[0.9850182,0.00008654139,0.01199605,0.001594592,0.0002980112,0.0001835903,0.000006273135,0.00002094205,0.0007958171],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9363529,"threshold_uncertainty_score":0.4687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.304014946362997,"score_gpt":0.5331454867421976,"score_spread":0.2291305403792006,"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."}}