{"id":"W4390873415","doi":"10.1109/iccv51070.2023.01202","title":"Examining Autoexposure for Challenging Scenes","year":2023,"lang":"en","type":"article","venue":"","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Canada First Research Excellence Fund","keywords":"Computer science; Shutter; Artificial intelligence; Point (geometry); Range (aeronautics); Computer vision; Software; Mathematics; Engineering","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":[0.0003415376,0.000069766,0.00007214575,0.0001196145,0.0000964604,0.00008501036,0.0004506479,0.0000265682,0.000009383935],"category_scores_gemma":[0.00003691608,0.00006411021,0.00002455599,0.0003009161,0.00000889998,0.0003386593,0.0001866317,0.00003240588,0.00006382218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001334821,"about_ca_system_score_gemma":0.00001322099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002018815,"about_ca_topic_score_gemma":8.608698e-7,"domain_scores_codex":[0.9992989,0.00000995714,0.0001035258,0.0002302158,0.0001163213,0.0002410879],"domain_scores_gemma":[0.99954,0.0000854059,0.00002401642,0.0002881932,0.00003780549,0.00002463018],"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":[0.000002586644,0.00003585789,0.0006083556,0.00009514089,0.00002626311,0.00002161493,0.001605161,0.0001018573,0.04114274,0.3460175,0.0495453,0.5607976],"study_design_scores_gemma":[0.0004360205,0.0003178827,0.003218356,0.00008056576,0.000004467889,0.000005519394,0.0002319573,0.6270484,0.3263915,0.01449952,0.02725351,0.0005122874],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002936714,0.00002623299,0.9864768,0.000766316,0.000211683,0.0001745254,3.145972e-7,0.00329155,0.006115865],"genre_scores_gemma":[0.6456914,0.00001991666,0.3497397,0.0002228614,0.00007473335,0.0001257532,0.00000245149,0.00001156338,0.00411161],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6427547,"threshold_uncertainty_score":0.2614339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0798597046753562,"score_gpt":0.2984972285027806,"score_spread":0.2186375238274244,"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."}}