{"id":"W7083454209","doi":"10.1109/tcsi.2025.3611874","title":"Noise Reduction in Charge-Sensitive Amplifiers for X-Ray Imagers With Large Line Capacitance","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Circuits and Systems I Regular Papers","topic":"Education, Psychology, and Social Research","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Petrochemical Research and Technology Company","keywords":"Parasitic capacitance; Linearity; Capacitance; Noise (video); Amplifier; CMOS; Noise reduction; Noise figure; Chip","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001324274,0.0001387473,0.0002446405,0.0002640711,0.0009527503,0.00009622674,0.0001021338,0.0001860667,0.00001774283],"category_scores_gemma":[0.00006652061,0.0001323026,0.00007040104,0.000594871,0.0004143355,0.0001535304,2.953554e-7,0.0002242267,0.000003267875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002599507,"about_ca_system_score_gemma":0.0003796981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001200328,"about_ca_topic_score_gemma":0.002283336,"domain_scores_codex":[0.9983155,0.0003467786,0.0002344609,0.0003982646,0.0002739836,0.0004309846],"domain_scores_gemma":[0.9991555,0.0002243878,0.00006333628,0.0001794872,0.0002241563,0.0001531353],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.001355348,0.003356757,0.002624875,0.001549862,0.001643967,0.00004710115,0.3936244,0.00519452,0.1380339,0.2549264,0.006597694,0.1910452],"study_design_scores_gemma":[0.01003673,0.00108376,0.005790099,0.001937525,0.0003388253,0.00002686442,0.7929077,0.0008945388,0.005619419,0.001372878,0.1781298,0.00186192],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.551263,0.001307478,0.3497546,0.01136624,0.008431125,0.006725613,0.0002858884,0.0002680687,0.07059799],"genre_scores_gemma":[0.9853534,0.0004809255,0.00002793383,0.0001145805,0.000154371,0.0002562969,0.000004332887,0.00001496253,0.0135932],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4340904,"threshold_uncertainty_score":0.7327881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0327746318233883,"score_gpt":0.3455289054260463,"score_spread":0.312754273602658,"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."}}