{"id":"W1526358376","doi":"10.1007/11559573_24","title":"Scalable e-Learning Multimedia Adaptation Architecture","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Multimedia Communication and Technology","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Transcoding; Computer science; Multimedia; Scalability; Adaptation (eye); Bitstream; Computer architecture; Overhead (engineering); Architecture; Modality (human–computer interaction); Content adaptation; Encoding (memory); Human–computer interaction; Computer network; Decoding methods; Artificial intelligence; Telecommunications; Ubiquitous computing; 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"],"consensus_categories":[],"category_scores_codex":[0.001150318,0.000286837,0.000328853,0.0007490441,0.0007109966,0.0001715028,0.001701912,0.0005951496,0.0004571076],"category_scores_gemma":[0.0006863407,0.0002869893,0.00008538774,0.0004658722,0.002063615,0.0001920406,0.0003995063,0.001549546,0.0001643983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003671382,"about_ca_system_score_gemma":0.0006810284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003623618,"about_ca_topic_score_gemma":0.005684095,"domain_scores_codex":[0.9974802,0.0001094457,0.0003475373,0.0006913404,0.0008071255,0.0005643229],"domain_scores_gemma":[0.9979178,0.0008040246,0.0002510166,0.0006496889,0.0002134827,0.0001640453],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003451549,0.00001368868,0.00004858451,0.00000493086,0.000004331027,0.000004527152,0.007236016,0.02100987,0.00002745059,0.008127919,0.00001243753,0.9635068],"study_design_scores_gemma":[0.0005182811,0.0001040579,0.0001111939,0.0003353634,0.00001812926,0.00001133625,0.0000203428,0.4435981,0.0002222715,0.09361722,0.4604941,0.0009496512],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00008221593,0.0006425412,0.9152925,0.005443035,0.0008270054,0.0004725626,0.000002450923,0.0003855896,0.07685208],"genre_scores_gemma":[0.3309316,0.0007767494,0.6576183,0.001284634,0.001506577,0.00002503752,0.00002920918,0.00006365145,0.007764198],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9625571,"threshold_uncertainty_score":0.9999582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02505015373113411,"score_gpt":0.2860627976483944,"score_spread":0.2610126439172603,"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."}}