{"id":"W2004052938","doi":"10.1080/2151237x.2009.10129276","title":"Visualizing High Dynamic Range Images in a Web Browser","year":2009,"lang":"en","type":"article","venue":"Journal of Graphics GPU and Game Tools","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Callback; JavaScript; Computer science; Computer graphics (images); Basis (linear algebra); Embedding; High dynamic range; Computer vision; Artificial intelligence; World Wide Web; Dynamic range; Mathematics; Programming language","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":[0.0004617467,0.0007834723,0.0003325989,0.0009848385,0.0002576841,0.001263535,0.0005758911,0.000631724,0.01540948],"category_scores_gemma":[0.001360161,0.0004118881,0.0003906046,0.0005341055,0.0002168451,0.001262959,0.001060146,0.0009721293,0.003798129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001564769,"about_ca_system_score_gemma":0.0003089159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008890773,"about_ca_topic_score_gemma":0.001685901,"domain_scores_codex":[0.9997625,0.00005494675,0.00001777074,0.00003736858,0.00009969393,0.00002786228],"domain_scores_gemma":[0.99911,0.0003723763,0.00004729517,0.0001556185,0.0002093842,0.0001052197],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007320481,0.0004534265,0.00278727,0.0007903203,0.0001340219,0.002059872,0.001781267,0.006353785,0.5128443,0.01074795,0.03864516,0.4226706],"study_design_scores_gemma":[0.0002730233,0.0007210308,0.01469498,0.0004852234,0.0001818346,0.007957619,0.0009554758,0.1526703,0.4946128,0.02302494,0.3040802,0.0003425453],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03731333,0.0005933825,0.91807,0.0003344398,0.00009594708,0.0001808774,0.0008184485,0.02978435,0.01280915],"genre_scores_gemma":[0.1814083,0.001081325,0.7953255,0.000255967,0.00007237604,0.0002250562,0.001135172,0.005752325,0.01474394],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01540948,"threshold_uncertainty_score":0.05154979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01215452792875708,"score_gpt":0.2781677793258045,"score_spread":0.2660132513970474,"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."}}