{"id":"W4416252369","doi":"10.1109/ijcnn64981.2025.11227405","title":"IllumiCurveNet: Low-Light Image Enhancement of Lunar Permanently Shadowed Regions Using a Self-Guided Loss Framework","year":2025,"lang":"","type":"article","venue":"","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Image enhancement; Noise (video); Image quality; Illuminance; Contrast (vision); Feature (linguistics); Attenuation; Camouflage; Contrast enhancement","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":[0.0003034128,0.000578624,0.000378123,0.0003229179,0.0001288389,0.0005377508,0.0008374849,0.0003688958,0.00138328],"category_scores_gemma":[0.0006238189,0.0001422787,0.0003039351,0.0001963353,0.0003092398,0.0006910774,0.0007773297,0.0006403475,0.0004929202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003038453,"about_ca_system_score_gemma":0.000382985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001153813,"about_ca_topic_score_gemma":0.002319732,"domain_scores_codex":[0.9998864,0.00001785715,0.000003652374,0.00002352468,0.00005352464,0.00001505703],"domain_scores_gemma":[0.9998485,0.0000446754,0.00001681605,0.00003057343,0.00004306027,0.00001641533],"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":[0.000467659,0.0002146423,0.001029422,0.0002678054,0.0001084101,0.0002772797,0.000136325,0.1141039,0.3287223,0.009163666,0.008766216,0.5367424],"study_design_scores_gemma":[0.00002475042,0.0002007379,0.0006672301,0.0000215705,0.0000315792,0.00037621,0.0000237342,0.8540139,0.1338027,0.00242072,0.008392143,0.00002462857],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04061617,0.000701611,0.952684,0.0001235561,0.00007300121,0.00004872157,0.0001026059,0.002241358,0.003409064],"genre_scores_gemma":[0.4112729,0.0008771611,0.5705922,0.0003244017,0.00006583516,0.00009504904,0.000696937,0.0006861254,0.01538943],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00138328,"threshold_uncertainty_score":0.004627526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01532279927838484,"score_gpt":0.3012156858857405,"score_spread":0.2858928866073557,"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."}}