{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":3,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":3,"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":"5a5e7bc6595d","filters":{"venue":"Journal of Artificial Intelligence and Technology"}},"results":[{"id":"W4225726538","doi":"10.37965/jait.2022.0102","title":"Artificial Intelligence and Applications","year":2022,"lang":"en","type":"article","venue":"Journal of Artificial Intelligence and Technology","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Artificial intelligence; Salience (neuroscience); Negotiation; Deep learning; Transformer; Language understanding; Domain (mathematical analysis); Applications of artificial intelligence; Data science; Machine learning; Natural language processing; Engineering","authors":[{"name":"Gang Hu","is_ca":false},{"name":"Bo Yu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04442778029422133,"gpt":0.292837138984283,"spread":0.2484093586900617,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006863925,0.0001248984,0.0002286847,0.0005561854,0.0004894983,0.0001001581,0.0006917753,0.00007827362,0.00002467094],"category_scores_gemma":[0.00009435284,0.0001220948,0.00004906043,0.00116846,0.0002734178,0.0001559175,0.0006820978,0.0006307848,0.000008000558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003068365,"about_ca_system_score_gemma":0.00007866453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004285338,"about_ca_topic_score_gemma":0.000006703817,"domain_scores_codex":[0.9985802,0.0000658105,0.0005994927,0.0002862916,0.0002184251,0.00024979],"domain_scores_gemma":[0.998915,0.0002151994,0.0003141211,0.0002299457,0.0002418963,0.0000838874],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001031912,0.00007285759,0.00007748252,0.000002608606,0.00001157317,0.00002221589,0.000145347,0.0003024182,0.000329486,0.287484,0.00002979991,0.7115119],"study_design_scores_gemma":[0.0000136254,0.0008098977,0.00003140898,0.00001975857,0.00001982846,0.0009413197,0.00170294,0.05233877,0.01498693,0.9220371,0.006886295,0.0002121773],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02736606,0.0015745,0.9659989,0.004400335,0.0003372092,0.0001284715,0.000001665546,0.00007189426,0.0001209667],"genre_scores_gemma":[0.991374,0.0002719493,0.007959269,0.0001593627,0.0001974169,0.00001688872,3.78886e-7,0.000006832956,0.00001386167],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.964008,"threshold_uncertainty_score":0.4978882,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4413952314","doi":"10.37965/jait.2025.0781","title":"A Multimodal Framework for Speech Emotion Recognition in Low-Resource Languages","year":2025,"lang":"en","type":"article","venue":"Journal of Artificial Intelligence and Technology","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Computer science; Resource (disambiguation); Emotion recognition; Speech recognition; Linguistics; Natural language processing","authors":[{"name":"Mamyr Altaibek","is_ca":false},{"name":"Altanbek Zulkhazhav","is_ca":false},{"name":"Banu Yergesh","is_ca":false},{"name":"Gulmira Bekmanova","is_ca":false},{"name":"Tileukhan Aibol","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04212576809165484,"gpt":0.3665315492201432,"spread":0.3244057811284884,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004018388,0.00009286592,0.000205466,0.0009540715,0.00005502846,0.00002014746,0.0001094915,0.000364546,0.0001281793],"category_scores_gemma":[0.0005133262,0.00008724779,0.0000611092,0.0005163161,0.0001115242,0.00006775602,0.00001990441,0.0003902728,0.00002539696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002865632,"about_ca_system_score_gemma":0.00002615481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001234058,"about_ca_topic_score_gemma":0.00005120829,"domain_scores_codex":[0.9990355,0.00005027171,0.000509813,0.0001595224,0.00006410761,0.0001808128],"domain_scores_gemma":[0.999271,0.0001992133,0.0002127629,0.0000971637,0.0001913981,0.00002845355],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002060253,0.000268123,0.0004691141,0.00002576886,0.0000324083,0.00002543191,0.0004376819,0.000005998343,0.001265304,0.05925028,0.0001391092,0.9378747],"study_design_scores_gemma":[0.000280106,0.0006375993,0.0006589371,0.0006496562,0.0000510654,0.000143877,0.01763028,0.0004997196,0.07355098,0.9046373,0.001099352,0.0001611435],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6837835,0.0004314157,0.309731,0.004035745,0.0006670707,0.0002644224,0.000006596575,0.00003973314,0.001040569],"genre_scores_gemma":[0.9896253,0.00007736781,0.009777875,0.0002415584,0.0001462611,0.00001471956,0.000004894804,0.000008042767,0.0001040028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9377136,"threshold_uncertainty_score":0.3557862,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4416912604","doi":"10.37965/jait.2025.0857","title":"Segmentation of Brain Tumor from Magnetic Resonance Imaging Using Handcrafted Features with BOA-Based Transformer","year":2025,"lang":"","type":"article","venue":"Journal of Artificial Intelligence and Technology","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Segmentation; Brain tumor; Magnetic resonance imaging; Pattern recognition (psychology); Image segmentation; Feature (linguistics); Neuroimaging","authors":[{"name":"M. Nagabushanam","is_ca":false},{"name":"V. N. Vinaykumar","is_ca":true},{"name":"Gavisiddappa","is_ca":false},{"name":"G. S. Nandeesh","is_ca":false},{"name":"M. P. Sundaresha","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02458216241339103,"gpt":0.2918778864232138,"spread":0.2672957240098228,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003757984,0.0002453944,0.000446163,0.001162909,0.0002606271,0.0001032237,0.0003255681,0.0001588791,0.00007955763],"category_scores_gemma":[0.0004295789,0.0002165069,0.00009108635,0.001967026,0.001138923,0.0002866435,0.00002132292,0.0006027407,0.000001743552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009133689,"about_ca_system_score_gemma":0.0003944898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006633029,"about_ca_topic_score_gemma":0.0001075541,"domain_scores_codex":[0.9977168,0.0001476041,0.00111087,0.0003994568,0.0003304597,0.0002948439],"domain_scores_gemma":[0.9981359,0.0003409047,0.000796291,0.0002406526,0.0004196456,0.00006662525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007531994,0.0001708685,0.001129616,0.0000350417,0.00001048126,0.00004345868,0.0002383632,0.0001627423,0.6726131,0.001816297,0.00002388306,0.3230029],"study_design_scores_gemma":[0.0003012937,0.0007744284,0.001424742,0.000629128,0.0001265061,0.0001427067,0.003700933,0.02323741,0.9611762,0.007950223,0.0003563227,0.0001801154],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.809725,0.005556778,0.1734987,0.0102333,0.0005317475,0.0003457637,0.00002269723,0.00002997353,0.00005596838],"genre_scores_gemma":[0.996293,0.0001917347,0.002795489,0.0006036053,0.0000465612,0.000004295577,7.320275e-7,0.00001586769,0.00004868639],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3228228,"threshold_uncertainty_score":0.8828896,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}