{"id":"W2097048977","doi":"10.1145/2461912.2461925","title":"Adaptive image synthesis for compressive displays","year":2013,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Advanced Optical Imaging Technologies","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Defense Advanced Research Projects Agency; Alfred P. Sloan Foundation","keywords":"Computer science; Rendering (computer graphics); High dynamic range; Computer vision; Stereoscopy; Computer graphics (images); Artificial intelligence; Light field; Compressed sensing; Set (abstract data type); Global illumination; Dynamic range","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.00002573529,0.0001699409,0.0001575034,0.0001592858,0.0001279673,0.000034823,0.0003190125,0.0001044662,0.00005043562],"category_scores_gemma":[0.0001059231,0.0001631855,0.0001106484,0.0002332951,0.0001811826,0.000299413,0.000004903389,0.0002788443,0.00005931646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003134421,"about_ca_system_score_gemma":0.000003999752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006844787,"about_ca_topic_score_gemma":0.000004612288,"domain_scores_codex":[0.9993176,0.000007310345,0.0001415523,0.0001776383,0.00009160901,0.0002642632],"domain_scores_gemma":[0.9986337,0.0007218267,0.00001774622,0.0004935073,0.00007898461,0.00005418641],"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":[0.0001830495,0.0009592035,0.0001122408,0.0007165652,0.001719203,0.00002586474,0.0006716638,0.1880295,0.0987424,0.04706908,0.01453023,0.647241],"study_design_scores_gemma":[0.0008017379,0.0002457328,0.000947337,0.0002221134,0.0002374169,0.00001337211,0.0007881389,0.4788724,0.2034466,0.3109687,0.002310768,0.001145709],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003562473,0.00006842935,0.9934103,0.000727936,0.0001383008,0.0003932541,0.00008775617,0.001205769,0.0004057935],"genre_scores_gemma":[0.7848502,0.0001556811,0.2140965,0.00005641795,0.00001003073,0.0007636448,0.000002125561,0.00004341019,0.00002200545],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7812877,"threshold_uncertainty_score":0.6654513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0176236540023535,"score_gpt":0.2382808043778286,"score_spread":0.2206571503754751,"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."}}