{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":5,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":5,"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":"d5e1e7be5d0e","filters":{"venue":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining"}},"results":[{"id":"W4206865191","doi":"10.1145/3488560.3498419","title":"Modeling Scale-free Graphs with Hyperbolic Geometry for Knowledge-aware Recommendation","year":2022,"lang":"en","type":"article","venue":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":69,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Huawei Technologies (Canada)","funders":"","keywords":"Knowledge graph; Computer science; Recommender system; Theoretical computer science; Semantics (computer science); Graph; Semantic space; ENCODE; Unification; Information retrieval; Artificial intelligence","authors":[{"name":"Yankai Chen","is_ca":false},{"name":"Meng‐Lin Yang","is_ca":false},{"name":"Yingxue Zhang","is_ca":true},{"name":"Mengchen Zhao","is_ca":false},{"name":"Ziqiao Meng","is_ca":false},{"name":"Jianye Hao","is_ca":false},{"name":"Irwin King","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1253498045435912,"gpt":0.3362451936795552,"spread":0.210895389135964,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007923273,0.0008795753,0.0008687055,0.001444296,0.0004320994,0.001268752,0.002139577,0.001342714,0.001302483],"category_scores_gemma":[0.005151938,0.0008606961,0.0009905886,0.001761583,0.0009649179,0.002914896,0.001126261,0.001641731,0.0006239363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001752593,"about_ca_system_score_gemma":0.0008697614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02203456,"about_ca_topic_score_gemma":0.02728573,"domain_scores_codex":[0.9993812,0.0001890542,0.00003065471,0.0002060689,0.0001354925,0.00005761248],"domain_scores_gemma":[0.9978037,0.001241945,0.0002671313,0.0003503094,0.0002584319,0.00007835137],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008172307,0.00005487773,0.002762571,0.0001344215,0.0001158684,0.000125312,0.0001843192,0.8675947,0.002451221,0.04811382,0.002581221,0.07579999],"study_design_scores_gemma":[0.000002955697,0.000008261488,0.0002130688,0.000004764241,0.000008576828,0.0000130544,0.000007744492,0.9861459,0.0002139984,0.0129052,0.0004700629,0.000006454949],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02309755,0.0005381147,0.973885,0.0002837816,0.000027181,0.0000279955,0.0002500336,0.0005314916,0.001358747],"genre_scores_gemma":[0.7542022,0.001313648,0.2380327,0.0003552503,0.00009952032,0.0001328198,0.001230335,0.0001581849,0.00447524],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02203456,"threshold_uncertainty_score":0.04381257,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4213235855","doi":"10.1145/3488560.3498387","title":"Translating Human Mobility Forecasting through Natural Language Generation","year":2022,"lang":"en","type":"article","venue":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"Australian Research Council","keywords":"Computer science; Bottleneck; Pipeline (software); Artificial intelligence; Natural language generation; Natural language; Machine learning; Mobility model; Data mining; Distributed computing","authors":[{"name":"Hao Xue","is_ca":false},{"name":"Flora D. Salim","is_ca":false},{"name":"Yongli Ren","is_ca":false},{"name":"Charles L. A. Clarke","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1311935183641742,"gpt":0.3313358354733655,"spread":0.2001423171091913,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001033332,0.000937629,0.0005075831,0.0008493145,0.0003832914,0.000708042,0.001451618,0.0008283526,0.002993952],"category_scores_gemma":[0.0054686,0.0004074717,0.0007472596,0.0008061808,0.000557036,0.001982463,0.001042181,0.001166177,0.00134193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000845357,"about_ca_system_score_gemma":0.001246983,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008067179,"about_ca_topic_score_gemma":0.007278068,"domain_scores_codex":[0.9994535,0.0001578093,0.00003206366,0.0002152502,0.00009753787,0.00004388062],"domain_scores_gemma":[0.9985103,0.000934594,0.00007656968,0.0002018664,0.0002417592,0.00003487867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002839039,0.0002756745,0.003541197,0.0002822515,0.00005852364,0.0004733587,0.0005533082,0.4958797,0.01051188,0.02254229,0.01682111,0.4487769],"study_design_scores_gemma":[0.00001404612,0.00003607158,0.0002259366,0.000008978052,0.000009922817,0.0000360828,0.00004257663,0.9807912,0.002965896,0.01299145,0.002866454,0.00001139972],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03765655,0.0001961404,0.9483357,0.0007756231,0.0001781381,0.0002330522,0.001130529,0.007975644,0.003518556],"genre_scores_gemma":[0.5065369,0.0003801667,0.4812418,0.0004087675,0.0001643597,0.0006581896,0.005566878,0.0004497953,0.004593191],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008067179,"threshold_uncertainty_score":0.01604044,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4212816054","doi":"10.1145/3488560.3498376","title":"An Ensemble Model for Combating Label Noise","year":2022,"lang":"en","type":"article","venue":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Artificial intelligence; Noise (video); Machine learning; Artificial neural network; Consistency (knowledge bases); Pattern recognition (psychology); Image (mathematics); Set (abstract data type); Matching (statistics); Measure (data warehouse); Function (biology); Data mining; Mathematics; Statistics","authors":[{"name":"Yangdi Lu","is_ca":true},{"name":"Bo Yang","is_ca":true},{"name":"Wenbo He","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1640580261696732,"gpt":0.3756783905798501,"spread":0.2116203644101769,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002320298,0.001362469,0.001526968,0.0009318787,0.0006263201,0.001053815,0.002737279,0.00217557,0.001407476],"category_scores_gemma":[0.005789895,0.0006250907,0.00105131,0.0008383285,0.0008507379,0.00357198,0.001861305,0.002708121,0.0006104966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008977166,"about_ca_system_score_gemma":0.0008551592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005502913,"about_ca_topic_score_gemma":0.007134654,"domain_scores_codex":[0.9990193,0.0002598546,0.00003952544,0.0003372939,0.0002325333,0.0001114787],"domain_scores_gemma":[0.9971803,0.001289728,0.0002988077,0.0004477613,0.0006611829,0.0001221075],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002515703,0.0001381461,0.002602093,0.00005184204,0.0001072487,0.0000986891,0.0001496029,0.8665044,0.00361193,0.0103623,0.002500292,0.1136219],"study_design_scores_gemma":[0.000003286626,0.00002155088,0.00008137539,0.000002814701,0.00001061569,0.000008193917,0.000003439185,0.9969268,0.0003087989,0.002446749,0.0001832487,0.000003108521],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05571728,0.0005393912,0.9403747,0.0005009222,0.00009349128,0.0000410657,0.0001544225,0.0008699702,0.001708643],"genre_scores_gemma":[0.8532011,0.0004708951,0.136778,0.0005031805,0.0002744091,0.0002313715,0.0007677271,0.0001847872,0.007588591],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005502913,"threshold_uncertainty_score":0.01227111,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4200631100","doi":"10.1145/3488560.3498498","title":"Differentially Private Ensemble Classifiers for Data Streams","year":2022,"lang":"en","type":"article","venue":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Data stream mining; Concept drift; Computer science; Competitor analysis; Data stream; Data mining; STREAMS; Private information retrieval; Black box; Ensemble forecasting; Machine learning; Regression; Artificial intelligence; Data modeling; Statistics; Database; Mathematics; Computer security","authors":[{"name":"Lovedeep Gondara","is_ca":true},{"name":"Ke Wang","is_ca":true},{"name":"Ricardo Silva Carvalho","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1680534875024225,"gpt":0.3582639277655094,"spread":0.1902104402630869,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007954455,0.001122002,0.002451836,0.001244319,0.001023847,0.002088165,0.002756871,0.002082474,0.001610824],"category_scores_gemma":[0.01940678,0.0005956648,0.001059106,0.001591722,0.001030356,0.005659007,0.003081664,0.004493326,0.0007773764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001549015,"about_ca_system_score_gemma":0.001550152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001509299,"about_ca_topic_score_gemma":0.001575507,"domain_scores_codex":[0.9957607,0.001239391,0.0002713524,0.0008969292,0.00145211,0.0003794509],"domain_scores_gemma":[0.9890175,0.005352222,0.0008302987,0.003001955,0.001462263,0.000335754],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000710766,0.0003223542,0.004173303,0.0001156196,0.0002060609,0.0001849426,0.0002387414,0.5996289,0.004489073,0.05398716,0.007126376,0.3288168],"study_design_scores_gemma":[0.00001154338,0.00002866909,0.0001259526,0.000006115072,0.00001223532,0.00002592614,0.000009283705,0.9789596,0.001035932,0.0190495,0.0007296163,0.000005707462],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01661728,0.0006764731,0.980325,0.0004510159,0.00009239967,0.00005960232,0.0001465241,0.0008205526,0.0008111151],"genre_scores_gemma":[0.7222908,0.0009402772,0.2690427,0.0005449965,0.0006394147,0.0003006633,0.001093137,0.0001922484,0.004955892],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007954455,"threshold_uncertainty_score":0.04206765,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4213017138","doi":"10.1145/3488560.3498507","title":"A GNN-based Multi-task Learning Framework for Personalized Video Search","year":2022,"lang":"en","type":"article","venue":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","topic":"Multimodal Machine Learning Applications","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":"Wilfrid Laurier University","funders":"","keywords":"Computer science; Task (project management); Human–computer interaction; Multimedia; Systems engineering; Engineering","authors":[{"name":"Li Zhang","is_ca":false},{"name":"Jiashu Zhao","is_ca":true},{"name":"Juan Yang","is_ca":false},{"name":"Tianshu Lyu","is_ca":false},{"name":"Dawei Yin","is_ca":false},{"name":"Haiping Lu","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1283070742733743,"gpt":0.3845772540133766,"spread":0.2562701797400023,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006732659,0.0008031589,0.0009601598,0.0006906166,0.0003125583,0.0004717618,0.001589783,0.001404967,0.001794912],"category_scores_gemma":[0.001793345,0.0003969188,0.0007007385,0.00124641,0.0004099825,0.001277019,0.0007206608,0.001248312,0.0005539408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001153094,"about_ca_system_score_gemma":0.0009557578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02721127,"about_ca_topic_score_gemma":0.02586659,"domain_scores_codex":[0.9997081,0.00007314131,0.00001496445,0.00009822621,0.00005023626,0.00005514034],"domain_scores_gemma":[0.9996641,0.0001402323,0.00003593782,0.00002862531,0.0001038501,0.00002724352],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001351739,0.0001301259,0.001273652,0.0000958758,0.00006694506,0.0001030705,0.00007047534,0.8579677,0.002535661,0.005909898,0.003732954,0.1279785],"study_design_scores_gemma":[0.00000336171,0.00001329642,0.00008381304,0.000001871898,0.000004471612,0.000008364587,0.000002946864,0.998145,0.00009918498,0.001484949,0.0001503265,0.000002353042],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0456238,0.00170836,0.9464028,0.0005752495,0.0001320598,0.00008369284,0.0003741056,0.001285026,0.003814843],"genre_scores_gemma":[0.84883,0.000725567,0.1402179,0.0004808306,0.0001546268,0.0001810519,0.0007668894,0.0001123567,0.008530758],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02721127,"threshold_uncertainty_score":0.05410576,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}