{"id":"W71245847","doi":"10.1145/2567948.2577315","title":"Learning to predict trending queries","year":2014,"lang":"en","type":"article","venue":"","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Task (project management); Baseline (sea); Architecture; Classifier (UML); Binary number; Volume (thermodynamics); Realization (probability); Data mining; Artificial intelligence; Information retrieval; Machine learning","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002575292,0.00006739881,0.000102551,0.00007852378,0.0001637825,0.0001839883,0.0003133897,0.00001722898,0.00009700311],"category_scores_gemma":[0.00009925436,0.00005419238,0.00004620521,0.0003269009,0.000009830256,0.0002643504,0.0002057895,0.00006063396,0.0001027136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009738163,"about_ca_system_score_gemma":0.000005562724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004100827,"about_ca_topic_score_gemma":0.00002030431,"domain_scores_codex":[0.9993243,0.00003108755,0.000120584,0.00020845,0.0001262837,0.0001892701],"domain_scores_gemma":[0.9996125,0.00004711841,0.0000325457,0.0002000076,0.00002379341,0.00008400338],"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":[0.000002554761,0.00001084083,0.006875407,0.000005395673,0.00002018,0.000001714126,0.002184283,0.007117109,0.00082899,0.225874,0.001551378,0.7555282],"study_design_scores_gemma":[0.00009053,0.0002632087,0.003472819,0.00001533073,0.000005704187,0.000005858441,0.0002810869,0.7851089,0.001098317,0.0005778928,0.2088754,0.0002048831],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02310941,0.000006368404,0.897849,0.0006380387,0.00009167795,0.00002229541,7.432425e-8,0.0002585935,0.07802455],"genre_scores_gemma":[0.9335692,8.623308e-7,0.05973668,0.0001760411,0.00007834921,0.000002643417,5.731246e-7,0.00000430387,0.006431338],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9104598,"threshold_uncertainty_score":0.2209901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008753699524768002,"score_gpt":0.2094982817541007,"score_spread":0.2007445822293327,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}