{"id":"W2107104233","doi":"10.1109/mwscas.1997.662261","title":"A BiCMOS VLSI implementation of an intelligent sensor","year":2005,"lang":"en","type":"article","venue":"","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Very-large-scale integration; Computer science; Interconnection; BiCMOS; Robustness (evolution); Modularity (biology); Artificial neural network; Embedded system; Computer architecture; Electronic engineering; Transistor; Engineering; Electrical engineering; Telecommunications; Artificial intelligence","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":[0.0001003242,0.0002371948,0.0001632203,0.0002225608,0.0002669394,0.0003305997,0.0006941368,0.0003925152,0.002389475],"category_scores_gemma":[0.000199897,0.0001782579,0.0001264933,0.000211149,0.000146847,0.000322725,0.0002434064,0.0002703376,0.0008024139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002744685,"about_ca_system_score_gemma":0.0002545668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007686456,"about_ca_topic_score_gemma":0.001466124,"domain_scores_codex":[0.9998543,0.00001560904,0.000006681506,0.00002434182,0.00007962369,0.0000193609],"domain_scores_gemma":[0.9998792,0.00001720432,0.00001010194,0.00001665447,0.00006689308,0.000009853874],"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":[0.0002381166,0.000124598,0.001351325,0.0003807777,0.00009282759,0.0006940319,0.0001630998,0.03635339,0.7113323,0.03866485,0.006513842,0.2040909],"study_design_scores_gemma":[0.0000974428,0.001002537,0.003172778,0.00008560096,0.0001404964,0.001913806,0.00007348126,0.4881976,0.4090345,0.01201154,0.08417666,0.00009366069],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1415043,0.001162744,0.8062103,0.0006073109,0.0004624758,0.0002299476,0.0004357163,0.004155238,0.04523198],"genre_scores_gemma":[0.6833026,0.0004244425,0.3018338,0.0003533489,0.00006013256,0.0001718227,0.0002487875,0.00004783007,0.01355729],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002389475,"threshold_uncertainty_score":0.007993519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009832033605743664,"score_gpt":0.2710363593279631,"score_spread":0.2612043257222195,"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."}}