{"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":"04cb2815c728","filters":{"venue":"Computing and Informatics"}},"results":[{"id":"W4389493777","doi":"10.31577/cai_2023_4_993","title":"Deep Learning Based Misogynistic Bangla Text Identification from Social Media","year":2023,"lang":"en","type":"article","venue":"Computing and Informatics","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Bengali; Hatred; Social media; Artificial intelligence; Computer science; Identification (biology); Deep learning; Confusion matrix; Hostility; Intimidation; Machine learning; Natural language processing; Psychology; World Wide Web; Social psychology; Political science","authors":[{"name":"Sonam Jahan","is_ca":false},{"name":"Raqeebir Rab","is_ca":false},{"name":"Peom Dutta","is_ca":false},{"name":"Hossain Muhammad Mahdi Hassan Khan","is_ca":false},{"name":"Muhammad Shahariar Karim Badhon","is_ca":false},{"name":"Sumaiya Binte Hassan","is_ca":true},{"name":"Ashikur Rahman","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01366158206172726,"gpt":0.2320620642814693,"spread":0.2184004822197421,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004026053,0.0000949298,0.0001166221,0.0001325056,0.0004911434,0.0003406553,0.0002424323,0.00006797976,0.000004725417],"category_scores_gemma":[0.0002146947,0.00009671861,0.00003319012,0.0004036898,0.00003350864,0.0002460195,0.0001218058,0.000174213,0.0002564311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001930447,"about_ca_system_score_gemma":0.00002289347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001071353,"about_ca_topic_score_gemma":0.000002640221,"domain_scores_codex":[0.9990926,0.00004469909,0.0003301151,0.000115747,0.0002049157,0.000211861],"domain_scores_gemma":[0.9992532,0.0003226973,0.0001632747,0.0001445896,0.000056047,0.00006026252],"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":[0.000005494574,0.00001991758,0.001006098,0.00009751085,0.00002301154,0.000005408568,0.03202079,0.01728775,0.0003373414,0.002170953,0.001361394,0.9456643],"study_design_scores_gemma":[0.0001900153,0.00001475905,0.01290681,0.00002045517,0.000005652302,0.000002174438,0.0006204296,0.9830474,0.000200923,0.0006000852,0.002273196,0.0001181384],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2628191,0.00002505329,0.7354637,0.0001086682,0.0004651589,0.00004793976,0.000001108481,0.0005281746,0.0005410666],"genre_scores_gemma":[0.9872003,0.00000876139,0.01244736,0.0001022366,0.0001460636,0.000001676957,0.00005202988,0.000006393137,0.00003520322],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9657596,"threshold_uncertainty_score":0.394407,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2911540882","doi":"10.4149/cai_2018_6_1411","title":"Using Probabilistic Temporal Logic PCTL and Model Checking for Context Prediction","year":2018,"lang":"en","type":"article","venue":"Computing and Informatics","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University of Edmonton; École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Probabilistic logic; Probabilistic CTL; Computer science; Model checking; Temporal logic; Context (archaeology); Probabilistic argumentation; Linear temporal logic; Theoretical computer science; Task (project management); Probabilistic relevance model; Artificial intelligence; Property (philosophy); Machine learning; Probabilistic analysis of algorithms","authors":[{"name":"Darine Ameyed","is_ca":true},{"name":"Moeiz Miraoui","is_ca":false},{"name":"Atef Zaguia","is_ca":false},{"name":"Fehmi Jaafar","is_ca":true},{"name":"Chakib Tadj","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1038689667459356,"gpt":0.3104117797728971,"spread":0.2065428130269615,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005426912,0.0001238913,0.0001884691,0.00008574306,0.0003561816,0.0002991841,0.0001494994,0.00006581327,2.960113e-7],"category_scores_gemma":[0.0001227859,0.0001153468,0.00002792773,0.0001071294,0.0001005386,0.0005820119,0.0002077191,0.00008132382,0.000001959584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003634728,"about_ca_system_score_gemma":0.00006150259,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001270732,"about_ca_topic_score_gemma":0.000004808387,"domain_scores_codex":[0.9990853,0.00002323411,0.000413373,0.0001511575,0.0001221169,0.0002047867],"domain_scores_gemma":[0.9991378,0.0001499815,0.0002366075,0.00018401,0.000218935,0.0000726685],"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":[0.00003447434,0.00009377373,0.00645125,0.001199244,0.00007892882,7.828982e-7,0.03967643,0.005052621,0.0003064694,0.02011643,0.0006822373,0.9263074],"study_design_scores_gemma":[0.0003934827,0.0001373747,0.0001405396,0.0001446876,0.000008816299,0.0000589158,0.0003456186,0.9952132,0.00006376451,0.002946738,0.0004178339,0.0001290307],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2131276,0.00003959307,0.7857875,0.00003510303,0.0002574552,0.00028442,0.000005576816,0.0001186547,0.0003441026],"genre_scores_gemma":[0.8934131,0.00000179964,0.1061966,0.0002231647,0.000140371,0.0000038877,0.000003154467,0.000005497435,0.00001246126],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9901606,"threshold_uncertainty_score":0.4703706,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}