{"id":"W1968571232","doi":"10.1145/1073204.1073242","title":"Evaluation of tone mapping operators using a High Dynamic Range display","year":2005,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":289,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sunnybrook Health Science Centre","funders":"","keywords":"Tone mapping; High dynamic range; Computer science; Contrast (vision); Visibility; High-dynamic-range imaging; Impression; Tone (literature); Brightness; Computer vision; Range (aeronautics); Artificial intelligence; Dynamic range; Computer graphics (images); Geography; Optics; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001027037,0.0001394794,0.0001468956,0.0004305773,0.0001739994,0.00004811498,0.0006203643,0.0000768098,0.0000327812],"category_scores_gemma":[0.00003175998,0.0001429125,0.00008751446,0.0009352396,0.00005993645,0.0007155975,0.00001427626,0.0001810149,0.00000555904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001558702,"about_ca_system_score_gemma":0.00009462461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005266298,"about_ca_topic_score_gemma":0.00009141326,"domain_scores_codex":[0.9983387,0.0001445042,0.0002826061,0.0002896957,0.0007531463,0.0001913645],"domain_scores_gemma":[0.9986675,0.00006228064,0.00009277663,0.0008160401,0.0003214798,0.00003993591],"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":[0.00002272801,0.001038141,0.0001508753,0.00006816571,0.0002692071,0.00000400735,0.002655839,0.02509426,0.1211711,0.00833385,0.00005951837,0.8411323],"study_design_scores_gemma":[0.0008146408,0.0001287299,0.001490898,0.000129039,0.0001379868,0.000009945832,0.00004157509,0.8861179,0.1059066,0.004720544,0.0001778563,0.0003242799],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.216672,0.00007762056,0.7821303,0.0005094154,0.0001466971,0.0002715868,0.000005505146,0.0001468503,0.00004005089],"genre_scores_gemma":[0.8120587,0.000061044,0.187666,0.0001409367,0.00001141972,0.00003805293,0.000001664316,0.0000105065,0.00001165379],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8610236,"threshold_uncertainty_score":0.5827804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04059747123573715,"score_gpt":0.3283221605109995,"score_spread":0.2877246892752623,"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."}}