{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":2,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":2,"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":"4a6157e4449e","filters":{"venue":"Contemporaneity of English Language and Literature in the Robotized Millennium"}},"results":[{"id":"W4396581097","doi":"10.46632/cellrm/3/1/1","title":"A Study on Mythological Approach of the Wizarding Saga antagonist Ensemble","year":2024,"lang":"en","type":"article","venue":"Contemporaneity of English Language and Literature in the Robotized Millennium","topic":"Folklore, Mythology, and Literature Studies","field":"Arts and Humanities","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":"Mythology; Originality; Harry potter; Phenomenon; Popularity; Meaning (existential); Publishing; Epistemology; Sociology; Literature; History; Psychology; Philosophy; Classics; Art history; Social science; Art; Social psychology","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.02996594938595796,"gpt":0.2607697177828739,"spread":0.230803768396916,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005397909,0.0003578271,0.0003933698,0.001994508,0.009945307,0.006905441,0.001566699,0.001908503,0.005468121],"category_scores_gemma":[0.01168174,0.0002652965,0.00031716,0.001380129,0.03134165,0.007268425,0.004838808,0.003760259,0.0005734392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003394508,"about_ca_system_score_gemma":0.001765444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003065947,"about_ca_topic_score_gemma":0.003946695,"domain_scores_codex":[0.9925004,0.005438883,0.0001130998,0.0006223914,0.0007929109,0.0005323407],"domain_scores_gemma":[0.9956722,0.002459137,0.0004759694,0.0004922608,0.0006356426,0.0002648393],"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":[0.00000676067,0.000009655992,0.0004813974,0.00001327204,0.000003066402,0.0001116076,0.1024467,0.00005249665,0.0001322095,0.8917166,0.001177979,0.003848235],"study_design_scores_gemma":[0.00001861418,0.0000764045,0.001753512,0.0002058615,0.00002052226,0.0008118404,0.2450774,0.002454718,0.0006907725,0.4599728,0.2888871,0.00003055155],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1975165,0.001330716,0.05271129,0.01716209,0.0004744171,0.00008869827,0.00003180092,0.00009123857,0.7305933],"genre_scores_gemma":[0.982767,0.0003034774,0.003165904,0.000564664,0.00007605395,0.00005380446,0.00001399622,0.00004978064,0.01300532],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009945307,"threshold_uncertainty_score":0.02854723,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4400215158","doi":"10.46632/cellrm/3/1/3","title":"Optimized Multimodal Emotional Recognition Using Long Short-Term Memory","year":2024,"lang":"en","type":"article","venue":"Contemporaneity of English Language and Literature in the Robotized Millennium","topic":"Music and Audio Processing","field":"Computer Science","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":"Mel-frequency cepstrum; Computer science; Speech recognition; Set (abstract data type); Feature extraction; Long short term memory; Feature (linguistics); Term (time); Recurrent neural network; Emotion recognition; Artificial intelligence; Artificial neural network","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.02074144888482584,"gpt":0.266578981233689,"spread":0.2458375323488632,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002668221,0.0006885861,0.0005401958,0.000345077,0.0002052003,0.0006023998,0.0005354875,0.0005015164,0.005500339],"category_scores_gemma":[0.0007624788,0.0001606604,0.0005597766,0.0003160127,0.000111393,0.0006311815,0.0004964941,0.0006189358,0.00224659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003228078,"about_ca_system_score_gemma":0.000347994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003316501,"about_ca_topic_score_gemma":0.004438889,"domain_scores_codex":[0.9998248,0.00002396359,0.000008966982,0.00006030505,0.00003621083,0.00004581479],"domain_scores_gemma":[0.999869,0.00003199756,0.000008907195,0.00001488165,0.0000640766,0.00001106506],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004955655,0.0001611932,0.0009493238,0.0001101609,0.0001143898,0.0001275082,0.00004145037,0.04873307,0.04162061,0.001116993,0.01530504,0.8912246],"study_design_scores_gemma":[0.00002212168,0.0002037468,0.001716445,0.00002282882,0.00007104517,0.00008784134,0.00005755894,0.9727706,0.01978499,0.001775562,0.003468546,0.00001865563],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1403933,0.00434172,0.8297858,0.0005962011,0.000787966,0.0001626629,0.001908256,0.007329652,0.01469456],"genre_scores_gemma":[0.8164517,0.001137407,0.1570425,0.0005718957,0.0001886252,0.0002538435,0.004648027,0.000257943,0.01944808],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005500339,"threshold_uncertainty_score":0.01840049,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}