{"id":"W2369936392","doi":"","title":"Texture Mapping Technology on VC","year":2008,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Simulation and Modeling Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"OpenGL; Computer science; Computer graphics (images); Texture mapping; Graphics; Texture (cosmology); Texture memory; Displacement mapping; Process (computing); Computer graphics; Texture atlas; Dimension (graph theory); Artificial intelligence; 3D computer graphics; Visualization; Software rendering; Image texture; Image processing; Image (mathematics); Programming language","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002191702,0.000124123,0.0001015086,0.0002318113,0.0002065151,0.00001237684,0.0002108865,0.0001050934,0.00002103087],"category_scores_gemma":[2.408686e-7,0.0001355055,0.00004152047,0.0004833404,0.00004181922,0.00003039508,0.00002571513,0.0001709859,0.000705626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004289199,"about_ca_system_score_gemma":0.00001141869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001026554,"about_ca_topic_score_gemma":5.266753e-7,"domain_scores_codex":[0.9993772,0.000003497124,0.0001757355,0.0002101642,0.00006442309,0.0001689716],"domain_scores_gemma":[0.9995197,0.00002395428,0.00001942235,0.0003383707,0.00004731967,0.00005124959],"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":[0.000002844459,0.000274023,0.0009421887,0.00005466535,0.00010538,0.000004079259,0.001008793,0.3813407,0.05898197,0.04259033,0.0649258,0.4497693],"study_design_scores_gemma":[0.0001756961,0.000005219866,0.0007116223,0.000007532698,0.000003654287,0.00003330985,0.00001397665,0.06501999,0.002576293,0.001057961,0.9302194,0.0001753622],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02223657,0.0001397338,0.9698525,0.0005348036,0.00001750252,0.0004457399,0.000009497514,0.001407725,0.005355914],"genre_scores_gemma":[0.8899577,0.00005051916,0.1082762,0.0004330178,0.0001770846,0.0007250601,0.0000438173,0.00003777439,0.0002988245],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8677211,"threshold_uncertainty_score":0.9069631,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01461336071533009,"score_gpt":0.2068610520795927,"score_spread":0.1922476913642626,"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."}}