{"id":"W7095105112","doi":"","title":"University of Alberta Content Adaptation Architecture for Universal Multimedia Access","year":2008,"lang":"en","type":"article","venue":"","topic":"Education, Technology, and Ethics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Adaptation (eye); Architecture; Exploit; Content adaptation; Cache; Proxy server; Proxy (statistics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005057012,0.00004380146,0.00005609187,0.00002263341,0.00009823596,0.000001542929,0.0001947156,0.00007300971,0.0006158019],"category_scores_gemma":[0.00005567758,0.00004245073,0.00002754656,0.00008751977,0.0003368859,0.0001054725,0.00005437187,0.00006085994,0.00001776092],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004835667,"about_ca_system_score_gemma":0.00002063731,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01303872,"about_ca_topic_score_gemma":0.02154298,"domain_scores_codex":[0.9996646,0.00001198845,0.00005123241,0.0001154031,0.00007084205,0.00008590802],"domain_scores_gemma":[0.9996806,0.0001278406,0.00004064931,0.0001040249,0.00001459958,0.00003225603],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003812987,0.000855675,0.7409464,0.00007234366,0.0001095593,0.000007769972,0.09726912,0.02148997,0.01374418,0.008472903,0.05472849,0.06192233],"study_design_scores_gemma":[0.003360576,0.0003958356,0.7308906,0.00002380759,0.00008461853,0.00002356672,0.03747044,0.03108176,0.01377216,0.00459516,0.1776622,0.0006392621],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9254538,0.000006450589,0.0607085,0.003699705,0.000108329,0.000247964,0.000005325831,0.00003674917,0.009733205],"genre_scores_gemma":[0.9809708,0.00003667466,0.01327131,0.00007096895,0.000008302714,5.708025e-7,0.00001076325,0.000003162818,0.005627475],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1229337,"threshold_uncertainty_score":0.9963113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07183422083048796,"score_gpt":0.2628513298637498,"score_spread":0.1910171090332619,"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."}}