{"id":"W4408863087","doi":"10.1109/icce63647.2025.10930110","title":"Energy-Conscious Image Enhancement for Dimmed Displays: Balancing Visual Quality and Power Efficiency for Consumer Devices","year":2025,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Quality (philosophy); Efficient energy use; Image quality; Power (physics); Image (mathematics); Electrical engineering; Computer vision; Physics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001602294,0.0003611317,0.0002557125,0.0003103101,0.0001732959,0.0007660741,0.0005827245,0.0003220835,0.001705706],"category_scores_gemma":[0.0005791818,0.0001642429,0.0002502774,0.000206778,0.0002688376,0.0009182715,0.0005880234,0.000461811,0.0002587662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000214264,"about_ca_system_score_gemma":0.0001283449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000186162,"about_ca_topic_score_gemma":0.0003965484,"domain_scores_codex":[0.9998658,0.00002432024,0.000005812848,0.00002783674,0.00006264438,0.00001347976],"domain_scores_gemma":[0.9997703,0.00007599093,0.00003652638,0.00003334136,0.00005930366,0.00002448725],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002042502,0.00008811492,0.000407681,0.0002119233,0.00002474618,0.00008546715,0.0001014371,0.001688435,0.9082761,0.001972879,0.0004487482,0.0864902],"study_design_scores_gemma":[0.00009854809,0.0009257238,0.008065367,0.0001014214,0.0001845848,0.001458043,0.0001383864,0.1127614,0.8552281,0.004256052,0.01667624,0.0001061589],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3088966,0.003180349,0.6791873,0.0003923203,0.0001263099,0.00009213613,0.00008218063,0.00102724,0.007015513],"genre_scores_gemma":[0.7234482,0.001233904,0.2707849,0.0003866793,0.0000992165,0.00004340413,0.00007828659,0.0001741937,0.003751385],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001705706,"threshold_uncertainty_score":0.005706131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01247939084128001,"score_gpt":0.3291503853628375,"score_spread":0.3166709945215574,"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."}}