{"id":"W4387678734","doi":"10.33693/2313-223x-2023-10-2-42-52","title":"IT Technologies in Health Care Institutions in Russia: Application with a Digital Interactive Map","year":2023,"lang":"en","type":"article","venue":"Computational nanotechnology","topic":"Economic and Technological Developments in Russia","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Informatization; Context (archaeology); Business; Digital transformation; Information technology; Adaptation (eye); Health care; Knowledge management; Institution; Information system; Process management; Engineering management; Computer science; Engineering; Political science; Economic growth; World Wide Web; Economics; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002131595,0.000111851,0.0001986528,0.0008374456,0.0002309805,0.0000357703,0.0003771727,0.000306466,0.000006495372],"category_scores_gemma":[0.0001933037,0.0001055333,0.00002003544,0.001690814,0.0006995604,0.0002224161,0.000159823,0.0003627025,0.000168463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006748804,"about_ca_system_score_gemma":0.0005279523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001315089,"about_ca_topic_score_gemma":0.001616251,"domain_scores_codex":[0.9988077,0.00003524042,0.0003228606,0.0003531985,0.0001322136,0.000348776],"domain_scores_gemma":[0.9995221,0.0001554507,0.0001218322,0.0001344748,0.00004257447,0.00002359804],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001497225,0.00007295432,0.01740832,0.00001748511,0.00001120496,0.00002567615,0.002316015,0.005055049,0.000001882638,0.8578407,0.0004239582,0.1168118],"study_design_scores_gemma":[0.00200541,0.0002705297,0.03719782,0.000335822,0.000003486717,0.00001530082,0.1424851,0.003300525,0.00006099513,0.3648728,0.4487153,0.0007369852],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4597062,0.0005820555,0.06840632,0.4289151,0.0003772922,0.002897172,0.0000935278,0.007060235,0.03196211],"genre_scores_gemma":[0.9958376,0.00006500234,0.003525435,0.0001610183,0.000006834905,0.0002174845,0.00007930355,0.000007134399,0.0001001482],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5361314,"threshold_uncertainty_score":0.4303521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02224053690686739,"score_gpt":0.3245956609603101,"score_spread":0.3023551240534427,"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."}}