{"id":"W2099091750","doi":"10.1109/iscas.1998.703891","title":"A robust hybrid neural architecture for an industrial sensor application","year":2002,"lang":"en","type":"article","venue":"","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"CMC Microsystems","keywords":"Artificial neural network; Computer science; Electronic engineering; CMOS; Electronic circuit; Resistor; Chip; Intelligent sensor; Engineering; Artificial intelligence; Electrical engineering; Wireless sensor network; Telecommunications","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":[0.0001548199,0.000186607,0.0001464992,0.0001310424,0.0001177429,0.0002564317,0.0005976762,0.0003877216,0.00122786],"category_scores_gemma":[0.0001529588,0.0001130695,0.0001234328,0.0001220102,0.0001380712,0.0003094749,0.0001934405,0.000186189,0.00036248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002855422,"about_ca_system_score_gemma":0.000217943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007835717,"about_ca_topic_score_gemma":0.00213527,"domain_scores_codex":[0.9998826,0.00001237655,0.000004284898,0.00003028434,0.00005764089,0.00001282224],"domain_scores_gemma":[0.9999349,0.00000949079,0.00001052074,0.00001151026,0.00002895167,0.000004677332],"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":[0.0002117835,0.00008530827,0.0006664163,0.0001410715,0.00005703654,0.0002052571,0.00003601918,0.1494861,0.6722972,0.00806017,0.001490341,0.1672633],"study_design_scores_gemma":[0.00003848438,0.0003915346,0.001401768,0.000009774191,0.00003667918,0.0002194277,0.0000098824,0.8799929,0.1102343,0.001858658,0.005784051,0.00002255456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2092613,0.0007132482,0.7760781,0.0002289221,0.00005748037,0.00006040488,0.0001091789,0.002027245,0.01146413],"genre_scores_gemma":[0.8380967,0.0001179345,0.1570501,0.00008751587,0.00001811075,0.00006054166,0.00008295941,0.00002139325,0.004464693],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00122786,"threshold_uncertainty_score":0.004107594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04594458726200766,"score_gpt":0.2137408563956229,"score_spread":0.1677962691336152,"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."}}