{"meta":{"query_hash":"36d23fe097a7","filters":{"venue":"Journal of Informatics and Web Engineering"},"cohort_total":1,"direct_labels_cover":0,"predictions_cover":1,"exported":1,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/36d23fe097a7","api":"https://metacan.xera.ac/api/v1/cohort?venue=Journal+of+Informatics+and+Web+Engineering"},"results":[{"id":"W4386629052","doi":"10.33093/jiwe.2023.2.2.6","title":"AIRA: An Intelligent Recommendation Agent Application for Movies","year":2023,"lang":"en","type":"article","venue":"Journal of Informatics and Web Engineering","topic":"Child Development and Digital Technology","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Drama; Limiting; Computer science; Psychology; Content (measure theory); Multimedia; Engineering","score_opus":0.022333190428857026,"score_gpt":0.28879738870088967,"score_spread":0.26646419827203266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386629052","genre_codex":"software","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07636064,0.006006598,0.38101897,0.0014371395,0.0010172483,0.004445807,0.01702228,0.4368721,0.075819194],"genre_scores_gemma":[0.23306452,0.004865886,0.5333348,0.0015179915,0.00032832942,0.0035568075,0.027468981,0.004940053,0.19092269],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996581,0.000060242284,0.000044673754,0.00006892619,0.0001416055,0.000026428143],"domain_scores_gemma":[0.9992924,0.00022923555,0.0000566645,0.00010307712,0.00022844486,0.000090112684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062089553,0.0010128056,0.0007089967,0.00095715985,0.0004693956,0.00080375536,0.0011557521,0.0010221516,0.027351398],"category_scores_gemma":[0.0022203107,0.00047935228,0.0005810626,0.0004653674,0.00009053402,0.0010856227,0.0007942697,0.00083264464,0.012240531],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017179976,0.0011756892,0.009087985,0.0016338775,0.00037487262,0.0010881666,0.0005933889,0.0024469956,0.029686678,0.0025938812,0.26889724,0.6807032],"study_design_scores_gemma":[0.0008761602,0.0013796771,0.027494105,0.0004696255,0.0005984771,0.0029722406,0.0004250558,0.15361816,0.029759092,0.003952843,0.77802825,0.0004263761],"about_ca_topic_score_codex":0.005217081,"about_ca_topic_score_gemma":0.009043382,"teacher_disagreement_score":0.027351398,"about_ca_system_score_codex":0.00027199715,"about_ca_system_score_gemma":0.00052569003,"threshold_uncertainty_score":0.09149957},"labels":[],"label_agreement":null}]}