{"id":"W7140021043","doi":"","title":"РІДКІ НЕЙРОННІ МЕРЕЖІ: ПРИНЦИП РОБОТИ ТА ОБЛАСТІ ЗАСТОСУВАННЯ","year":2024,"lang":"uk","type":"article","venue":"A.N.Beketov KNUME Digital Repository (National University of Kharkiv)","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Technische Universität Wien; Universität Wien; Institute for Catastrophic Loss Reduction","keywords":"Process (computing); Identification (biology); Product (mathematics)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.001661037,0.0004376841,0.0003519581,0.001622642,0.001731125,0.005073207,0.000654492,0.001222195,0.02569283],"category_scores_gemma":[0.004789977,0.0005626638,0.0003610332,0.001956997,0.002719962,0.002543856,0.001635079,0.001822001,0.01035455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00156734,"about_ca_system_score_gemma":0.002284757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002360487,"about_ca_topic_score_gemma":0.002817418,"domain_scores_codex":[0.998178,0.000375437,0.0000833907,0.0002573626,0.0009015124,0.0002043052],"domain_scores_gemma":[0.9983333,0.0005252206,0.0001621996,0.0003136594,0.0005147186,0.0001509055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002329776,0.0001089357,0.001881265,0.0005555851,0.000032879,0.0009674009,0.002576071,0.001535384,0.01421321,0.7179108,0.02602789,0.2339575],"study_design_scores_gemma":[0.00006666301,0.0001367997,0.002782667,0.0004578043,0.00006493538,0.001814612,0.002598034,0.002237899,0.02025259,0.2765558,0.6929128,0.000119431],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06338069,0.01881495,0.1433251,0.01359919,0.002249279,0.0003023727,0.0008822224,0.0007885019,0.7566577],"genre_scores_gemma":[0.7658053,0.0143184,0.09218848,0.0008978081,0.0005794529,0.000466917,0.0004069816,0.0005452122,0.1247914],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02569283,"threshold_uncertainty_score":0.08595103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006531272292883377,"score_gpt":0.1775173867789942,"score_spread":0.1709861144861108,"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."}}