{"id":"W4248568606","doi":"10.1007/978-3-540-76778-7_6","title":"Correlation-Based Content Adaptation for Mobile Web Browsing","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Adaptation (eye); Content adaptation; Web content; Fidelity; World Wide Web; Resource (disambiguation); Multimedia; Mobile device; Web page; Human–computer interaction; Ubiquitous computing; Computer network","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":[0.001050339,0.0006073646,0.001300165,0.001127647,0.0004763669,0.0007906074,0.001389505,0.0009330142,0.002778179],"category_scores_gemma":[0.004452994,0.0004413503,0.0006388461,0.001792778,0.0003370513,0.00112885,0.0008741091,0.001067225,0.001496906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00064005,"about_ca_system_score_gemma":0.0006131176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01004926,"about_ca_topic_score_gemma":0.01507084,"domain_scores_codex":[0.9991392,0.0002336719,0.00004424849,0.0002163925,0.0002791145,0.00008732848],"domain_scores_gemma":[0.998026,0.0009868144,0.0001071303,0.0003179075,0.0004831993,0.00007912167],"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":[0.001063243,0.0007362568,0.003959022,0.0002146845,0.0002366923,0.0001799225,0.0001585474,0.1465405,0.0467413,0.003006981,0.01034003,0.7868228],"study_design_scores_gemma":[0.00001873769,0.00006221535,0.001709601,0.000007471856,0.00003450871,0.0000744596,0.00001538773,0.991066,0.005209639,0.0009072983,0.0008738413,0.00002084372],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06487107,0.00178265,0.9238628,0.0001510027,0.0001770145,0.0001440749,0.0003076246,0.005561417,0.003142277],"genre_scores_gemma":[0.7349446,0.0007135541,0.2575774,0.0001456448,0.0002059069,0.0001574201,0.000617264,0.0004902343,0.005148009],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01004926,"threshold_uncertainty_score":0.0199815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06438257793434539,"score_gpt":0.2798464742769874,"score_spread":0.2154638963426421,"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."}}