{"id":"W2912737350","doi":"10.22215/etd/2007-08305","title":"A CMOS imaging device for visual prosthetics using on-pixel gray-scale erosion for edge detection","year":2007,"lang":"en","type":"dissertation","venue":"","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; The Debajehmujig Creation Centre (Canada); Canadian Heritage; Library and Archives Canada","funders":"","keywords":"Pixel; Grayscale; CMOS; Computer graphics (images); Enhanced Data Rates for GSM Evolution; Gray (unit); Computer science; Computer vision; Artificial intelligence; Engineering; Electrical engineering; Nuclear medicine; Medicine","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":[0.0002251541,0.0003250777,0.0002514465,0.0003636648,0.0002250281,0.0005265491,0.000646698,0.0006190956,0.008294555],"category_scores_gemma":[0.0003235336,0.0002027077,0.0002170865,0.0002090048,0.0002024568,0.0005130882,0.0003251146,0.0004622613,0.001920168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002148558,"about_ca_system_score_gemma":0.0004046358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003446034,"about_ca_topic_score_gemma":0.0008442175,"domain_scores_codex":[0.999836,0.000008472603,0.000007881908,0.00003184435,0.00009997251,0.00001579118],"domain_scores_gemma":[0.9998403,0.00003365964,0.00001432122,0.00002746921,0.00006300754,0.00002123664],"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":[0.00006440005,0.0001002364,0.0001661757,0.000138664,0.00001070065,0.0001287817,0.00007208524,0.0002186016,0.8911721,0.001747158,0.003746794,0.1024343],"study_design_scores_gemma":[0.00005086916,0.0006771086,0.004456428,0.00006318801,0.00004769022,0.002342943,0.0000579869,0.01177347,0.8928992,0.0007245202,0.08686533,0.00004133314],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1531595,0.00357281,0.7946844,0.0009466241,0.0009449843,0.0006036694,0.0006298816,0.003962655,0.04149551],"genre_scores_gemma":[0.2796948,0.00257299,0.6282374,0.0005750242,0.0001338537,0.0002264301,0.0005612145,0.0002414698,0.08775676],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008294555,"threshold_uncertainty_score":0.02774805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01385454886631223,"score_gpt":0.3096049972614792,"score_spread":0.295750448395167,"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."}}