{"id":"W4321325571","doi":"10.1002/adma.202210715","title":"A Wafer‐Scale Nanoporous 2D Active Pixel Image Sensor Matrix with High Uniformity, High Sensitivity, and Rapid Switching","year":2023,"lang":"en","type":"article","venue":"Advanced Materials","topic":"2D Materials and Applications","field":"Materials Science","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; National Research Foundation of Korea; National Research Foundation; Korea Health Industry Development Institute; Compute Canada","keywords":"Nanoporous; Materials science; Active matrix; Wafer; Optoelectronics; Image sensor; Dot pitch; Transistor; Bilayer; Pixel; Molybdenum disulfide; Nanotechnology; Optics; Thin-film transistor; Voltage; Electrical engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009349352,0.0003397622,0.0001802393,0.0002698329,0.0001349144,0.0002634138,0.0003600103,0.0003188918,0.0007851106],"category_scores_gemma":[0.000118724,0.0002901761,0.0001984769,0.00009925679,0.000168244,0.0002467694,0.0002518751,0.0002998458,0.0004037961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002605437,"about_ca_system_score_gemma":0.0001881905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004144273,"about_ca_topic_score_gemma":0.001000147,"domain_scores_codex":[0.999891,0.000005825688,0.000004834564,0.00003297082,0.00005427998,0.00001107728],"domain_scores_gemma":[0.9999143,0.00001416814,0.00002035688,0.00001299473,0.00001812987,0.00002007448],"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":[0.000003590734,0.000004563075,0.00003511691,0.000010565,0.000001983175,0.00001224933,0.000002478024,0.00004237964,0.9992454,0.00003130197,0.00003008037,0.0005803069],"study_design_scores_gemma":[0.000005809848,0.0000547107,0.0008295385,0.000001293825,0.000006127527,0.0001132332,0.000005840334,0.002153768,0.9948062,0.0000197549,0.001997619,0.000006051377],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9301308,0.001125179,0.0598079,0.0002629555,0.0001315392,0.0001288346,0.001523404,0.001908807,0.004980633],"genre_scores_gemma":[0.9190701,0.0004352931,0.07609198,0.00007608777,0.00003235069,0.0001033906,0.0009378415,0.00006817986,0.003184851],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007851106,"threshold_uncertainty_score":0.002626479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006961889255606046,"score_gpt":0.2504919651624482,"score_spread":0.2435300759068422,"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."}}