{"id":"W4393864600","doi":"10.11603/mie.1996-1960.2023.3-4.14471","title":"РОЗРОБЛЕННЯ МОДЕЛІ МАШИННОГО НАВЧАННЯ ДЛЯ ДИФЕРЕНЦІЙНОЇ ДІАГНОСТИКИ ТРАНЗИТОРНИХ ВТРАТ СВІДОМОСТІ СИНКОПАЛЬНОГО ТА НЕСИНКОПАЛЬНОГО ПОХОДЖЕННЯ У ДІТЕЙ","year":2024,"lang":"uk","type":"article","venue":"Medical Informatics and Engineering","topic":"Epilepsy research and treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003858726,0.000950011,0.0005642545,0.002490105,0.005540792,0.01323311,0.001513972,0.003176164,0.04706633],"category_scores_gemma":[0.01201879,0.0008166408,0.0008997078,0.002290606,0.01007875,0.008601357,0.005508095,0.004323631,0.01570821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005575059,"about_ca_system_score_gemma":0.009691039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009093802,"about_ca_topic_score_gemma":0.009132552,"domain_scores_codex":[0.9939599,0.00180109,0.0003411708,0.001048359,0.002198064,0.0006514069],"domain_scores_gemma":[0.9944277,0.001639431,0.0004625799,0.0009236201,0.001939257,0.000607483],"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":[0.00006095497,0.00004802618,0.001780588,0.00031496,0.00002931543,0.0004652206,0.008554435,0.0005705748,0.0018238,0.9205297,0.01699069,0.04883172],"study_design_scores_gemma":[0.00003039356,0.00005259495,0.003637754,0.0006148448,0.00004963607,0.0005696187,0.01085694,0.001096818,0.002649131,0.3461768,0.6341665,0.00009903105],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02419685,0.005859221,0.08125132,0.02091538,0.001636161,0.0002646334,0.000790844,0.0004763924,0.8646092],"genre_scores_gemma":[0.5649207,0.009537588,0.108511,0.004392056,0.001033782,0.0009243877,0.00096908,0.001087224,0.3086241],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04706633,"threshold_uncertainty_score":0.1574526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01117047701723338,"score_gpt":0.2736551110942241,"score_spread":0.2624846340769907,"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."}}