{"id":"W4236518274","doi":"10.32920/ryerson.14645022","title":"A CMOS voltage-mode image sensing system","year":2021,"lang":"en","type":"preprint","venue":"","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"CMOS; Image sensor; Electronic engineering; Pixel; CMOS sensor; Correlated double sampling; Electronic circuit; SIGNAL (programming language); Noise (video); Electrical engineering; Computer science; Voltage; Engineering; Image (mathematics); Artificial intelligence; Amplifier","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009420452,0.0003809177,0.0004684451,0.0001018465,0.00004705524,0.0003511185,0.0001782063,0.0002314718,0.00007147567],"category_scores_gemma":[0.0000197612,0.0004029248,0.0002131964,0.0001081755,0.00002695802,0.00007172568,0.0002881924,0.0007042864,0.0001221219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002384075,"about_ca_system_score_gemma":0.00004900793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003481073,"about_ca_topic_score_gemma":0.00005164813,"domain_scores_codex":[0.9986212,0.00002574097,0.0003340211,0.000433604,0.0002192686,0.0003661294],"domain_scores_gemma":[0.9989798,0.00003416272,0.00003883734,0.0007502975,0.00009319281,0.0001037066],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000164076,0.00008805922,0.0002111515,0.02469198,0.001766132,0.004949433,0.007304585,0.4371521,0.4007857,0.00123494,0.06972828,0.05207121],"study_design_scores_gemma":[0.0002039764,0.000002952867,0.00007826698,0.001330531,0.0001053242,0.0001913815,0.002193934,0.9634908,0.02878864,0.00004766305,0.002662688,0.0009037734],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4283571,0.001283158,0.3890406,0.0001272908,0.008468245,0.0005394225,0.00006244233,0.007709651,0.1644121],"genre_scores_gemma":[0.9830998,0.00003567043,0.01459642,0.00004710102,0.0003973422,0.000005469732,0.00006802176,0.0001315703,0.001618654],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5547426,"threshold_uncertainty_score":0.9998423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00693671533621491,"score_gpt":0.2188569410911364,"score_spread":0.2119202257549215,"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."}}