{"id":"W2101234418","doi":"10.1109/ted.2005.856192","title":"Reset and Partition Noise in Active Pixel Image Sensors","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Electron Devices","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Reset (finance); Transistor; Noise (video); Partition (number theory); Pixel; Electronic engineering; Computer science; Noise measurement; Flicker noise; Noise generator; Noise floor; Electrical engineering; Engineering; Artificial intelligence; Mathematics; CMOS; Noise figure; Noise reduction; Voltage; Image (mathematics)","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":[],"consensus_categories":[],"category_scores_codex":[0.0000625605,0.0001520341,0.0001326285,0.000187398,0.00006784142,0.00003748473,0.00005297653,0.00005911542,0.00005130796],"category_scores_gemma":[0.000001569342,0.00016238,0.00003692224,0.0002187326,0.00003592798,0.0003415519,3.037261e-7,0.0003047008,0.00006457149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001130349,"about_ca_system_score_gemma":0.000009810831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003026914,"about_ca_topic_score_gemma":0.001125127,"domain_scores_codex":[0.999217,0.00002934924,0.0001543185,0.000186787,0.0001097945,0.0003026927],"domain_scores_gemma":[0.9997334,0.00005059504,0.00001667706,0.0001237732,0.00001772521,0.00005785422],"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":[0.000274122,0.0004013684,0.0001601351,0.000168441,0.000162515,0.00002043666,0.003008037,0.3449192,0.5103092,0.00008707895,0.0007588154,0.1397307],"study_design_scores_gemma":[0.0009881102,0.0001297812,0.003751464,0.00008371091,0.00005244071,0.00003753642,0.0002908458,0.09310307,0.8916783,0.0001024541,0.009260204,0.0005221235],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900448,0.0001514474,0.007500216,0.0004124885,0.00008469077,0.0001281158,0.00001830166,0.0002425539,0.001417335],"genre_scores_gemma":[0.9991332,0.000262312,0.0002870237,0.00007300696,0.00004707482,0.00002471271,0.000002694214,0.00002839868,0.0001415943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.381369,"threshold_uncertainty_score":0.6621663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005939933650472447,"score_gpt":0.2274032282264604,"score_spread":0.221463294575988,"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."}}