{"id":"W4414514211","doi":"10.1002/adfm.202513092","title":"Artificial Compound Eye for Clear Vision in Harsh Environment","year":2025,"lang":"en","type":"article","venue":"Advanced Functional Materials","topic":"Surface Roughness and Optical Measurements","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Alberta Innovates; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Engineering and Physical Sciences Research Council; Canada Foundation for Innovation","keywords":"Machine vision; Compound eye; Crawling; Tracking (education); Night vision; Motion (physics); Match moving; Pixel; Optical imaging","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001257131,0.0002682303,0.0002234057,0.0001497955,0.0001030647,0.0002667936,0.0001635035,0.0002818886,0.0009307049],"category_scores_gemma":[0.0002541067,0.0001171376,0.0002514384,0.0000846924,0.0001969362,0.0003184194,0.0002609591,0.000226659,0.0001837597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000175478,"about_ca_system_score_gemma":0.0001794735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008493897,"about_ca_topic_score_gemma":0.00140219,"domain_scores_codex":[0.9999324,0.000007006446,0.000002560412,0.00002353692,0.00002405272,0.00001049179],"domain_scores_gemma":[0.9998531,0.00004650511,0.00003513056,0.00001701705,0.00003264681,0.00001545111],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006312702,0.00002057458,0.000592909,0.0000703202,0.0000137663,0.00007498458,0.00001820097,0.004492333,0.9775433,0.0003495005,0.0002424672,0.01651846],"study_design_scores_gemma":[0.00002198612,0.00066015,0.008807286,0.00001704127,0.00003983477,0.0005040839,0.00003495329,0.2072469,0.7767709,0.0005636846,0.005287502,0.0000456667],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8910071,0.001065672,0.1039379,0.00008794404,0.00006264319,0.00004641424,0.0001583663,0.0004931688,0.003140863],"genre_scores_gemma":[0.9599832,0.0002573344,0.03795332,0.00003725641,0.000007996804,0.00001399624,0.00007439654,0.00001747542,0.001655027],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009307049,"threshold_uncertainty_score":0.003113508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01657520747830408,"score_gpt":0.2486002557197663,"score_spread":0.2320250482414623,"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."}}