{"id":"W7062883304","doi":"","title":"Зарубіжний досвід використання штучного інтелекту в правосудді","year":2025,"lang":"en","type":"article","venue":"Scientific periodicals of Ukraine","topic":"Adaptive optics and wavefront sensing","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nucleofection; Work (physics); Government (linguistics); Filter (signal processing); Frame (networking); Relevance (law)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006306624,0.0002259006,0.0004007624,0.0002367376,0.0005158817,0.000251508,0.0003683132,0.00006251459,0.001103749],"category_scores_gemma":[0.00006491847,0.0002050372,0.0002271097,0.0006353745,0.0009388356,0.0001336137,0.0002203077,0.0001968583,0.00008907789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002739188,"about_ca_system_score_gemma":0.0002555475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008559971,"about_ca_topic_score_gemma":0.000007823619,"domain_scores_codex":[0.9980665,0.00005447932,0.0004990618,0.0005479396,0.0003748023,0.0004572336],"domain_scores_gemma":[0.9987152,0.00008966269,0.0001660287,0.0006099595,0.0002699755,0.0001491273],"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":[0.0001399637,0.001506789,0.02545083,0.0001984065,0.0006124551,0.00001963315,0.002852795,0.0003284196,0.1624395,0.5746047,0.1043563,0.1274903],"study_design_scores_gemma":[0.002306247,0.0001374967,0.007792208,0.0004776156,0.0001852823,0.000001985434,0.001577665,0.01082388,0.04873867,0.03048297,0.896536,0.0009399659],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8287805,0.0005872632,0.01878954,0.001926733,0.00191822,0.0004210068,0.0002166891,0.00007495816,0.1472851],"genre_scores_gemma":[0.9769868,0.000003245702,0.002675194,0.00009922202,0.0001421117,0.000006692303,0.00007815863,0.00001511912,0.01999346],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7921798,"threshold_uncertainty_score":0.9998094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009656889736462563,"score_gpt":0.2658557124379334,"score_spread":0.2561988227014709,"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."}}