{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0005370613,0.0002497995,0.0001861853,0.0003725094,0.0003851627,0.001093651,0.002261715,0.0001005959,0.00001998901],"category_scores_gemma":[0.00005296754,0.0002654294,0.00009918589,0.0004790411,0.00004325327,0.001702173,0.0008602347,0.000462844,0.00004872278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000141136,"about_ca_system_score_gemma":0.00008594573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009008982,"about_ca_topic_score_gemma":0.000008650436,"domain_scores_codex":[0.9978063,0.00001041947,0.0004943457,0.0007576096,0.0005778646,0.0003535222],"domain_scores_gemma":[0.9981046,0.00009793886,0.0002206652,0.0002487742,0.001166962,0.0001610695],"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":[0.00006914551,0.0003659744,0.05715781,0.00007429061,0.0001978587,0.000009714669,0.001160495,0.01311632,0.001440812,0.3896953,0.000791308,0.535921],"study_design_scores_gemma":[0.0003350566,0.0000480073,0.001175759,0.000054082,0.00001089204,0.00005837481,0.00001870814,0.9810319,0.0001723791,0.00633797,0.01048405,0.0002728441],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01104471,0.00008732106,0.9837428,0.0006043175,0.000470422,0.0003263602,0.00001278215,0.0011419,0.002569439],"genre_scores_gemma":[0.9303505,0.00006853964,0.06826784,0.0003675534,0.0004868289,0.000124478,0.00006527144,0.00001920783,0.0002497587],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9679156,"threshold_uncertainty_score":0.9999798,"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."}}