{"meta":{"query_hash":"bbb9d391bb98","filters":{"venue":"International Journal of Data Mining & Knowledge Management Process"},"cohort_total":2,"direct_labels_cover":0,"predictions_cover":2,"exported":2,"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/bbb9d391bb98","api":"https://metacan.xera.ac/api/v1/cohort?venue=International+Journal+of+Data+Mining+%26+Knowledge+Management+Process"},"results":[{"id":"W2527711547","doi":"10.5121/ijdkp.2016.6501","title":"Using Ontology Based Semantic Association Rule Mining in Location Based Services","year":2016,"lang":"en","type":"article","venue":"International Journal of Data Mining & Knowledge Management Process","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Association rule learning; Ontology; Information retrieval; Data mining; Data science","score_opus":0.05422144218284687,"score_gpt":0.35759145911862394,"score_spread":0.3033700169357771,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2527711547","genre_codex":"methods","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":[0.091776535,0.00069486175,0.90000486,0.0007089337,0.00012038525,0.00045678078,0.00091962004,0.0016510601,0.003666997],"genre_scores_gemma":[0.41305405,0.0006381094,0.5836541,0.00017551909,0.00003744066,0.00027310583,0.0014378721,0.00006652899,0.0006633289],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9939348,0.0019667316,0.00088789477,0.0008031717,0.0020655554,0.0003418285],"domain_scores_gemma":[0.99585754,0.0022438022,0.0004472962,0.0004680454,0.00085023756,0.0001330131],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038600143,0.00063598354,0.0009576405,0.0050231586,0.0013654747,0.0025515568,0.0014037157,0.0010324828,0.00081340375],"category_scores_gemma":[0.010404681,0.00043752458,0.0021958025,0.005722946,0.0008732974,0.0037708804,0.0017593313,0.0010590183,0.00045204343],"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":[0.0006213871,0.0017452522,0.05115607,0.001181704,0.001113278,0.0031147976,0.0025810318,0.14127396,0.015845735,0.06677837,0.0060039293,0.7085844],"study_design_scores_gemma":[0.000051556926,0.00011648322,0.0052417624,0.00015420558,0.0003563793,0.00084346696,0.00097267475,0.9179438,0.012492655,0.0485698,0.0131669175,0.00009034002],"about_ca_topic_score_codex":0.01214003,"about_ca_topic_score_gemma":0.013654685,"teacher_disagreement_score":0.01214003,"about_ca_system_score_codex":0.0010334965,"about_ca_system_score_gemma":0.00285445,"threshold_uncertainty_score":0.024138749},"labels":[],"label_agreement":null},{"id":"W2795656879","doi":"10.5121/ijdkp.2018.8203","title":"Increased Prediction Accuracy in the Game of Cricket Using Machine Learning","year":2018,"lang":"en","type":"article","venue":"International Journal of Data Mining & Knowledge Management Process","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":71,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Laurentian University","funders":"","keywords":"Cricket; Computer science; Artificial intelligence; Machine learning","score_opus":0.108082120679226,"score_gpt":0.34502539577942604,"score_spread":0.23694327510020002,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795656879","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9510777,0.0006879058,0.04129274,0.00075255154,0.00019655355,0.000060058752,0.0013685228,0.00084040384,0.0037235783],"genre_scores_gemma":[0.98898137,0.00011654046,0.008295668,0.000041844723,0.000029577082,0.0000163309,0.0014603272,0.000022232678,0.0010361237],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99838984,0.0005292831,0.00014391242,0.0003686361,0.0003351496,0.00023327634],"domain_scores_gemma":[0.9891629,0.008497052,0.00060277426,0.00038907735,0.0010021889,0.00034595275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035363752,0.0008580094,0.00080437673,0.0019867793,0.00043913178,0.001490341,0.00072415813,0.0010622067,0.0015851092],"category_scores_gemma":[0.013054777,0.00018961451,0.0005752698,0.0012785443,0.0003109693,0.0011500458,0.00053266855,0.0014097033,0.00071103213],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012072673,0.00077493495,0.27279085,0.00022344074,0.00023149584,0.0003278177,0.0001832283,0.5016723,0.0017304177,0.0013024822,0.0068024164,0.21275336],"study_design_scores_gemma":[0.0000086903265,0.00013525614,0.02365772,0.000022082906,0.000017535182,0.000035429337,0.000057182864,0.9738756,0.0009574249,0.00087439147,0.0003430782,0.000015638172],"about_ca_topic_score_codex":0.02136468,"about_ca_topic_score_gemma":0.0149174025,"teacher_disagreement_score":0.02136468,"about_ca_system_score_codex":0.00087512244,"about_ca_system_score_gemma":0.00071499735,"threshold_uncertainty_score":0.042480648},"labels":[],"label_agreement":null}]}