{"id":"W4361190416","doi":"10.1002/advs.202207661","title":"Self‐Curable Synaptic Ferroelectric FET Arrays for Neuromorphic Convolutional Neural Network","year":2023,"lang":"en","type":"article","venue":"Advanced Science","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Samsung; Ministry of Science and ICT, South Korea; Seoul National University; National Research Foundation","keywords":"Neuromorphic engineering; Materials science; Ferroelectricity; Computer science; Convolutional neural network; Transistor; Long-term potentiation; Synapse; Artificial neural network; Electronic engineering; Optoelectronics; Artificial intelligence; Electrical engineering; Neuroscience; Engineering; Chemistry; Voltage","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003441911,0.0001881637,0.0001836028,0.0001475907,0.0006620384,0.00004120846,0.0004116582,0.00003438394,0.000004073607],"category_scores_gemma":[0.0001816032,0.0001948663,0.00005889683,0.002511235,0.0001434035,0.0006144363,0.00006358921,0.000216066,0.00003684451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009250252,"about_ca_system_score_gemma":0.00005467522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.155185e-7,"about_ca_topic_score_gemma":9.679161e-7,"domain_scores_codex":[0.9981097,0.00001556129,0.0002226137,0.0004212408,0.0002703829,0.0009604768],"domain_scores_gemma":[0.9991366,0.0003481467,0.00004604983,0.0002358368,0.00008555759,0.0001478576],"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":[0.000009741338,0.000004873787,0.00003771266,0.00003362223,0.000004517836,0.000009264555,0.00002676602,0.9439302,0.05285547,0.001132606,0.0002485597,0.00170663],"study_design_scores_gemma":[0.0003130347,0.0001048624,0.000571012,0.00001962774,0.000007642299,0.000037224,0.00001419737,0.9840517,0.008759066,0.003458098,0.002402887,0.0002606651],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9497653,0.0004394887,0.04366184,0.0001287251,0.00243646,0.0005808254,0.000009614757,0.002473495,0.0005042811],"genre_scores_gemma":[0.9921092,0.00005755748,0.007333516,0.000125712,0.0001993477,0.00003540354,0.00000796577,0.00003186055,0.00009948348],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0440964,"threshold_uncertainty_score":0.7946418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02649516279339481,"score_gpt":0.2501657385188678,"score_spread":0.223670575725473,"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."}}