{"id":"W4410260480","doi":"10.52058/2786-6025-2025-4(45)-1286-1298","title":"ПІДБІР КРИТЕРІЇВ ОЦІНКИ ТА ПРОВЕДЕННЯ ПОРІВНЯЛЬНОГО АНАЛІЗУ ВЕЛИКИХ МОДЕЛЕЙ ШТУЧНОГО ІНТЕЛЕКТУ DEEPSEEK ТА CHATGPT","year":2025,"lang":"uk","type":"article","venue":"Наука і техніка сьогодні","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Institute for Catastrophic Loss Reduction","keywords":"Computer science","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":[0.001838105,0.0004503879,0.0001937275,0.001390964,0.002265839,0.006633759,0.0005706896,0.001301876,0.01774579],"category_scores_gemma":[0.004923835,0.0004654684,0.0002934128,0.001352732,0.004739917,0.002352906,0.002317662,0.002325024,0.006031115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002940701,"about_ca_system_score_gemma":0.005454948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008172729,"about_ca_topic_score_gemma":0.01055299,"domain_scores_codex":[0.9972619,0.0007326722,0.0001168945,0.0002753312,0.001334393,0.0002789327],"domain_scores_gemma":[0.9981393,0.000625505,0.000120355,0.0003215052,0.0005987901,0.000194626],"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":[0.00005168613,0.00002820065,0.001116234,0.0001614872,0.0000103031,0.0002686216,0.01075349,0.0005752759,0.002498172,0.9053949,0.005560544,0.07358111],"study_design_scores_gemma":[0.00003158577,0.00008057621,0.005022265,0.0003295044,0.00003781425,0.0005650717,0.010889,0.0009347045,0.005015526,0.2434872,0.733522,0.00008471352],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0573931,0.003584052,0.08443397,0.007991134,0.001094881,0.0001866344,0.0003260861,0.0004011509,0.8445889],"genre_scores_gemma":[0.7879407,0.003655167,0.04909984,0.0005529885,0.0003534462,0.0003736737,0.0002107396,0.0003557606,0.1574576],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01774579,"threshold_uncertainty_score":0.05936557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004891088753394681,"score_gpt":0.2114476570658201,"score_spread":0.2065565683124254,"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."}}