{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":1,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":1,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"4a1675ac217e","filters":{"venue":"Cybersecurity Education Science Technique"}},"results":[{"id":"W4387402209","doi":"10.28925/2663-4023.2023.21.6574","title":"MULTIPLE EFFECTIVENESS CRITERIA OF FORMING DATABASES OF EMOTIONAL VOICE SIGNALS","year":2023,"lang":"en","type":"article","venue":"Cybersecurity Education Science Technique","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Context (archaeology); Database; Affective computing; Computer science; Speech recognition; Psychology; Artificial intelligence","authors":[{"name":"Ivan Dychka","is_ca":false},{"name":"Ihor Tereikovskyi","is_ca":false},{"name":"Andrii Samofalov","is_ca":false},{"name":"Lyudmila Tereykovska","is_ca":false},{"name":"Vitaliy A. Romankevich","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06962682235063221,"gpt":0.4231073413656374,"spread":0.3534805190150052,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01049192,0.001261502,0.002360577,0.00732142,0.001656518,0.005282529,0.003487371,0.001746656,0.01102466],"category_scores_gemma":[0.06118678,0.0008647248,0.001991904,0.003363472,0.001535102,0.00454041,0.004108138,0.001101097,0.002368275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001771433,"about_ca_system_score_gemma":0.001586413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002157048,"about_ca_topic_score_gemma":0.001570429,"domain_scores_codex":[0.9890062,0.002796729,0.00156405,0.001489319,0.004347072,0.0007967007],"domain_scores_gemma":[0.9587149,0.02547391,0.001636281,0.002922415,0.01023079,0.001021644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002130504,0.0003771683,0.01050895,0.001374398,0.0002974538,0.0007079174,0.001485874,0.05814641,0.0326748,0.1885466,0.006839283,0.6969107],"study_design_scores_gemma":[0.000215336,0.001305036,0.01041751,0.0003986384,0.0004881792,0.001208798,0.001826188,0.7842751,0.06068011,0.1122347,0.02677287,0.0001776093],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06458674,0.001487911,0.9168002,0.0003607416,0.00009279476,0.000727152,0.0008658035,0.0006437199,0.01443503],"genre_scores_gemma":[0.4437972,0.0006556936,0.5447581,0.0001011134,0.0001634884,0.001213719,0.002462781,0.0005510302,0.006296886],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01102466,"threshold_uncertainty_score":0.05548728,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}