{"id":"W2135786084","doi":"10.1109/compsac.2007.136","title":"Machine Learning Prediction andWeb Access Modeling","year":2007,"lang":"en","type":"article","venue":"Proceedings - International Computer Software & Applications Conference","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University","funders":"","keywords":"Computer science; Machine learning; Cache; Artificial intelligence; Sequence (biology); Predictive modelling; Scheme (mathematics); Extension (predicate logic); Data mining; Operating system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002247609,0.0008186697,0.0008563934,0.001218439,0.0004373563,0.001081887,0.001065887,0.001218866,0.001342389],"category_scores_gemma":[0.009812518,0.0004008791,0.0005246161,0.002065968,0.000658511,0.001645454,0.0004644594,0.001462507,0.0004259065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001215623,"about_ca_system_score_gemma":0.0007730095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01550636,"about_ca_topic_score_gemma":0.009666121,"domain_scores_codex":[0.9990283,0.0004039398,0.00005387122,0.0001858955,0.0002285599,0.00009944615],"domain_scores_gemma":[0.9936385,0.004909664,0.000438563,0.0003837622,0.0005452064,0.00008433896],"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":[0.00005274961,0.0000761921,0.004437798,0.00003911537,0.00004508984,0.00004889552,0.00003046047,0.9473568,0.000289636,0.005719274,0.0008602425,0.04104379],"study_design_scores_gemma":[0.000001940308,0.000006399865,0.0002893456,0.000002559874,0.000002473762,0.000007373987,0.00000238179,0.9955682,0.0001380993,0.003858118,0.0001201589,0.000003018222],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08118848,0.001100352,0.9127806,0.001096992,0.00009403927,0.0000612529,0.0004471343,0.001248991,0.001982279],"genre_scores_gemma":[0.9088415,0.0007238176,0.08655136,0.0001284331,0.0001847188,0.0001523985,0.0006811368,0.00005996611,0.002676748],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01550636,"threshold_uncertainty_score":0.03083217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03343103169845864,"score_gpt":0.2711120882522849,"score_spread":0.2376810565538263,"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."}}