{"id":"W4404645655","doi":"10.1038/s41598-024-80272-x","title":"Charge-trap synaptic device with polycrystalline silicon channel for low power in-memory computing","year":2024,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Science and ICT, South Korea; National Research Foundation","keywords":"Trap (plumbing); Polycrystalline silicon; Channel (broadcasting); Charge (physics); Computer science; Optoelectronics; Power (physics); Silicon; Materials science; Electrical engineering; Physics; Nanotechnology; Computer network; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009193321,0.0001581621,0.0001972288,0.0001202856,0.0001768212,0.0003187231,0.001094896,0.0002998135,0.00333912],"category_scores_gemma":[0.0003263278,0.00008425515,0.0001237589,0.0003092248,0.0001622494,0.0006053307,0.0001790956,0.0002622393,0.0002635397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003923207,"about_ca_system_score_gemma":0.0005065905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001271133,"about_ca_topic_score_gemma":0.003429205,"domain_scores_codex":[0.9999502,0.000005682574,0.000002478599,0.0000105129,0.0000199148,0.00001123557],"domain_scores_gemma":[0.9998645,0.00004123823,0.00002177392,0.00002158966,0.00003587883,0.00001494583],"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":[0.001002765,0.0007936731,0.006932752,0.001503674,0.0002694873,0.001751911,0.0001865925,0.17522,0.6867642,0.02859052,0.01909181,0.07789274],"study_design_scores_gemma":[0.0001829479,0.001656071,0.003932999,0.000057315,0.0001662455,0.0004380694,0.0001112644,0.6550438,0.3207086,0.003787149,0.01385358,0.0000619206],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9435887,0.001397375,0.03998157,0.0005434048,0.0004879386,0.00008724919,0.0006770965,0.0009877982,0.01224884],"genre_scores_gemma":[0.983648,0.0002450001,0.01419163,0.00007719194,0.00001511853,0.00004612745,0.0001165684,0.00002549543,0.001634913],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00333912,"threshold_uncertainty_score":0.01117045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01260374285195802,"score_gpt":0.2421973414453752,"score_spread":0.2295935985934172,"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."}}