{"id":"W1994854360","doi":"10.1145/1164783.1164814","title":"A buffer management technique for 3D image-based rendering on mobile devices","year":2006,"lang":"en","type":"article","venue":"","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Rendering (computer graphics); Mobile device; Image-based modeling and rendering; Tiled rendering; Mobile telephony; Parallel rendering; Artificial intelligence; Computer vision; Real-time computing; Software rendering; Mobile radio; Computer network; 3D computer graphics; Computer graphics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007281618,0.0007790691,0.0006082385,0.0008500593,0.0006023828,0.001422285,0.002375944,0.000690404,0.004074895],"category_scores_gemma":[0.002681192,0.0004825902,0.0004974105,0.0007195323,0.0005132872,0.002334975,0.001487204,0.001020355,0.001004184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000504903,"about_ca_system_score_gemma":0.0006638324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001610685,"about_ca_topic_score_gemma":0.001496693,"domain_scores_codex":[0.9995229,0.00008072142,0.00005270225,0.00008636663,0.0002040164,0.00005337126],"domain_scores_gemma":[0.9990813,0.0001993294,0.0001267738,0.0003415474,0.0001847097,0.00006644571],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009891124,0.0001535924,0.001027877,0.0005118801,0.0001296619,0.0008391151,0.001080345,0.01521827,0.4048318,0.04371798,0.01552674,0.5159736],"study_design_scores_gemma":[0.0002456202,0.000876383,0.001495293,0.0001445556,0.0002507185,0.002567982,0.0002577743,0.4196691,0.4669719,0.01136924,0.09585879,0.0002925781],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006874216,0.0004628671,0.9871039,0.00009730892,0.0001103493,0.0001076321,0.0000744003,0.004140147,0.001029201],"genre_scores_gemma":[0.2697433,0.0006715407,0.7223071,0.0002020196,0.0001549334,0.0002715734,0.0003153132,0.0007779,0.005556297],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004074895,"threshold_uncertainty_score":0.01363188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01318649094648493,"score_gpt":0.2851633423851551,"score_spread":0.2719768514386702,"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."}}