{"id":"W2338434056","doi":"10.1109/tvlsi.2015.2474706","title":"Racetrack Memory-Based Nonvolatile Storage Elements for Multicontext FPGAs","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Very Large Scale Integration (VLSI) Systems","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Non-volatile memory; Field-programmable gate array; Computer science; Embedded system; Parallel computing; Very-large-scale integration; Semiconductor memory; Non-volatile random-access memory; Computer hardware; Memory refresh; Computer architecture; Computer memory","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":[0.0004666356,0.0003472222,0.000376898,0.0002192531,0.0002725589,0.00009976942,0.0001832132,0.0001780326,0.00003881762],"category_scores_gemma":[0.00002347846,0.0003386306,0.0001971636,0.0002571939,0.00002762927,0.0004898139,0.000001078326,0.0003934883,0.0001107062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003344066,"about_ca_system_score_gemma":0.00004977968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001576835,"about_ca_topic_score_gemma":0.0001487551,"domain_scores_codex":[0.9981082,0.0001050207,0.0006399946,0.0003629167,0.0003385601,0.0004453037],"domain_scores_gemma":[0.9988433,0.0002102643,0.0001138657,0.0003760772,0.0002355422,0.000221005],"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":[0.0001324438,0.0001647186,0.00001141598,0.0001328122,0.00004863805,0.000004140798,0.0006603684,0.9756558,0.01712621,0.00001376213,0.001062225,0.004987461],"study_design_scores_gemma":[0.002010666,0.0001901214,0.000006081792,0.000187922,0.00003949345,0.000007084734,0.001160608,0.8476954,0.1447774,0.000009735724,0.003581489,0.0003340477],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.153456,0.000114644,0.8402482,0.00002316401,0.004161452,0.0009772695,0.0002172968,0.0005185904,0.0002833881],"genre_scores_gemma":[0.9958214,0.000004620609,0.002266859,0.00007381034,0.0002275766,0.0003058305,0.00004931198,0.00007959706,0.001171065],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8423653,"threshold_uncertainty_score":0.9999066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03265050515637805,"score_gpt":0.2663978201855771,"score_spread":0.2337473150291991,"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."}}