{"id":"W1833441044","doi":"10.1007/3-540-45348-2_27","title":"Delivering Adaptive Web Content Based on Client Computing Resources","year":2001,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; XML; Dynamic web page; Architecture; World Wide Web; Web service; Web content; Web server; Server-side; Operating system; Distributed computing; Web page; The Internet","routes":{"ca_aff":true,"ca_fund":true,"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"],"consensus_categories":[],"category_scores_codex":[0.001526937,0.0008897141,0.0008931739,0.001078407,0.0005558496,0.0009310794,0.004432723,0.0003861122,0.00001788014],"category_scores_gemma":[0.00009061761,0.0008175347,0.0002898213,0.0008879471,0.0005369987,0.000292998,0.001424677,0.001205501,0.0001196983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006377603,"about_ca_system_score_gemma":0.0005359633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009206575,"about_ca_topic_score_gemma":0.00005381879,"domain_scores_codex":[0.9937085,0.0001223941,0.0009336773,0.002332565,0.001739251,0.001163622],"domain_scores_gemma":[0.9958283,0.001031804,0.0006311031,0.001770951,0.0004072278,0.0003306684],"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":[0.00002500926,0.00006655828,0.0001567757,0.00003730818,0.00001956315,0.0003065644,0.0006607626,0.7559217,0.00004166147,0.009120116,0.00003734431,0.2336066],"study_design_scores_gemma":[0.0005636206,0.0005206723,0.0002153747,0.001702683,0.000008600648,0.00007050643,6.631886e-7,0.9876217,0.0001056301,0.00297636,0.005304648,0.0009095897],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001057539,0.0003092782,0.9787261,0.0003802247,0.002522486,0.0005580816,0.00001448178,0.0004428768,0.01598893],"genre_scores_gemma":[0.8768892,0.00001293988,0.1201842,0.001869092,0.0007724346,0.000005729919,0.00001063092,0.00005228007,0.0002034807],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8758317,"threshold_uncertainty_score":0.9994276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03633550635861978,"score_gpt":0.2378816971487744,"score_spread":0.2015461907901546,"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."}}