{"id":"W2107985063","doi":"10.1109/ted.2003.818156","title":"Above-threshold parameter extraction and modeling for amorphous silicon thin-film transistors","year":2003,"lang":"en","type":"article","venue":"IEEE Transactions on Electron Devices","topic":"Thin-Film Transistor Technologies","field":"Engineering","cited_by":127,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Thin-film transistor; Amorphous silicon; Materials science; Threshold voltage; Optoelectronics; Transistor; Extraction (chemistry); Saturation (graph theory); Amorphous solid; Fabrication; Silicon; Electron mobility; Band gap; Contact resistance; Oxide thin-film transistor; Electronic engineering; Voltage; Layer (electronics); Crystalline silicon; Electrical engineering; Nanotechnology; Engineering","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":[0.0001799957,0.0003967457,0.0003459991,0.0003350939,0.0002520163,0.00007321873,0.0001645453,0.0003235294,0.00002719305],"category_scores_gemma":[0.00000774335,0.000421839,0.0001822476,0.0002732027,0.00006489409,0.0004265899,2.590537e-7,0.0005933706,0.000009651272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002029292,"about_ca_system_score_gemma":0.00002922804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000300819,"about_ca_topic_score_gemma":0.0004701556,"domain_scores_codex":[0.9983575,0.00002953474,0.0003783204,0.0004567319,0.0002044134,0.0005734882],"domain_scores_gemma":[0.999312,0.0001647542,0.00004227697,0.0003405199,0.00004763979,0.00009277838],"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":[0.00008324943,0.0001168464,0.00001684709,0.0002024588,0.000184945,0.000002961189,0.0003709653,0.9268367,0.06570539,0.0003589917,0.00008087482,0.006039782],"study_design_scores_gemma":[0.0008658684,0.000299745,0.00003268624,0.00005299455,0.000222097,0.0000460781,0.0002286198,0.5100792,0.4834916,0.0008492121,0.00316697,0.0006648811],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5154103,0.001432143,0.4808414,0.00006840619,0.0004675517,0.0004086988,0.00002209778,0.00111662,0.0002327351],"genre_scores_gemma":[0.9958527,0.0005130183,0.003073396,0.00007324154,0.00002224513,0.0002548801,0.000003232509,0.000108487,0.00009877063],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4804424,"threshold_uncertainty_score":0.9998233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01792891490317274,"score_gpt":0.2411192091563888,"score_spread":0.223190294253216,"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."}}