{"id":"W2114548500","doi":"10.1109/ccece.2005.1557439","title":"Low frequency noise in amorphous silicon thin-film transistors","year":2006,"lang":"en","type":"article","venue":"","topic":"Thin-Film Transistor Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"University of Waterloo","keywords":"Thin-film transistor; Noise (video); Amorphous silicon; Transistor; Materials science; Silicon; Optoelectronics; Amorphous solid; Noise power; Detector; Saturation (graph theory); Flicker noise; Johnson–Nyquist noise; Physics; Electrical engineering; Power (physics); Voltage; Computer science; Nanotechnology; Noise figure; Optics; Crystallography; CMOS; Chemistry; Engineering; Crystalline silicon; Artificial intelligence; Quantum mechanics; Mathematics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009343912,0.0002870646,0.0002972525,0.0003158919,0.00003529021,0.00002598873,0.0003395248,0.0002715897,0.0001966667],"category_scores_gemma":[0.00001455346,0.0002909079,0.000107534,0.0004341041,0.00009315976,0.0002077695,0.000009965028,0.0003832316,0.000128525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002651332,"about_ca_system_score_gemma":0.00001792088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001328608,"about_ca_topic_score_gemma":0.004761455,"domain_scores_codex":[0.9986596,0.0000154642,0.0003966492,0.0002856729,0.0001888118,0.0004538756],"domain_scores_gemma":[0.9994384,0.000038619,0.00002005492,0.0004401038,0.00001831911,0.00004451549],"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":[0.00002549631,0.0003628989,0.01301759,0.000434564,0.00005902778,0.0003660251,0.0009651819,0.3365734,0.6141074,0.01361742,0.01453694,0.0059341],"study_design_scores_gemma":[0.003290826,0.0001846162,0.1447563,0.0002232643,0.00007504084,0.00006235626,0.0006388649,0.04433409,0.7816058,0.01305071,0.008953976,0.002824171],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9548839,0.001067934,0.002549757,0.000184959,0.000463407,0.0002465596,0.00001550755,0.004244834,0.03634311],"genre_scores_gemma":[0.9966553,0.00004376188,0.002708151,0.00004159318,0.00003939322,0.00003703532,0.000009426121,0.00007040385,0.0003949404],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2922393,"threshold_uncertainty_score":0.9999543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005258649260123111,"score_gpt":0.1756897631005979,"score_spread":0.1704311138404748,"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."}}