{"id":"W4238371118","doi":"10.1109/tdpvt.2004.1335305","title":"Adaptive online transmission of 3D texmesh using scale-space analysis","year":2004,"lang":"en","type":"article","venue":"Proceedings. 2nd International Symposium on 3D Data Processing, Visualization and Transmission, 2004. 3DPVT 2004.","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Bandwidth (computing); Preprocessor; Image texture; Artificial intelligence; Visualization; Computer vision; Feature (linguistics); Pattern recognition (psychology); Algorithm; Image processing; Image (mathematics)","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":[0.0003599674,0.000454555,0.0005510994,0.0008166132,0.000292255,0.000716473,0.0007321157,0.0003756312,0.002025085],"category_scores_gemma":[0.002365395,0.0002905232,0.0005207753,0.0006813584,0.0003907011,0.0009901277,0.0008767557,0.000483936,0.0005020526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002922431,"about_ca_system_score_gemma":0.000237121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001256422,"about_ca_topic_score_gemma":0.001262073,"domain_scores_codex":[0.9996362,0.0000459681,0.00001852742,0.00004584574,0.0002302257,0.00002335879],"domain_scores_gemma":[0.998898,0.000445743,0.0001125317,0.000331615,0.000170094,0.00004204841],"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":[0.0004712215,0.00009024995,0.002229583,0.0001372684,0.00007339831,0.0004050543,0.0003829232,0.1645938,0.2706802,0.006646696,0.00302592,0.5512636],"study_design_scores_gemma":[0.00002122488,0.00007500836,0.001225153,0.000005037622,0.00001966093,0.0002880782,0.00005356732,0.9363225,0.05632563,0.002665662,0.002976691,0.00002178679],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02572916,0.0000800206,0.9720058,0.00004740115,0.00002536402,0.0000277735,0.00003721211,0.001336516,0.0007108107],"genre_scores_gemma":[0.3729742,0.0003233569,0.6231249,0.00005903927,0.00006621386,0.0000861747,0.000341702,0.000592959,0.002431626],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002025085,"threshold_uncertainty_score":0.006774604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02549089350250072,"score_gpt":0.2946599124108755,"score_spread":0.2691690189083748,"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."}}