{"id":"W2164251202","doi":"10.1109/mtdt.2005.17","title":"An Investigation into Three-Level Ferroelectric Memory","year":2005,"lang":"en","type":"article","venue":"","topic":"Semiconductor materials and devices","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; CMC Microsystems","keywords":"Ferroelectric RAM; Non-volatile memory; Semiconductor memory; Flash memory; Computer science; Computer data storage; Memory cell; Computer memory; Computer hardware; SIGNAL (programming language); Flash (photography); Non-volatile random-access memory; Data retention; Ferroelectricity; Memory refresh; Electrical engineering; Materials science; Optoelectronics; Engineering; Physics; Transistor; Voltage","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":[0.0001763754,0.0001615834,0.0002766834,0.0002311128,0.0004399775,0.0008737648,0.0006611039,0.0005193739,0.003744352],"category_scores_gemma":[0.0006049703,0.00009242774,0.0002687084,0.0003890831,0.0004304629,0.001276207,0.0005048898,0.0004443281,0.0004799149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003160429,"about_ca_system_score_gemma":0.0002872942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004549035,"about_ca_topic_score_gemma":0.0004435615,"domain_scores_codex":[0.9998522,0.00001522672,0.00000533771,0.00001982697,0.00005935967,0.00004802249],"domain_scores_gemma":[0.9997382,0.0001001805,0.00003048778,0.0000423541,0.0000693911,0.00001946709],"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":[0.0004335893,0.0003990844,0.003578123,0.0006022961,0.0000293958,0.001026319,0.0007548911,0.00683523,0.8267397,0.09691858,0.001540468,0.06114241],"study_design_scores_gemma":[0.00004252451,0.000986867,0.003218536,0.00006233334,0.00003879948,0.001396404,0.0006660037,0.07027006,0.8810253,0.01736235,0.02488307,0.00004785357],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9181516,0.003385214,0.04007208,0.001161118,0.0001054046,0.0001202574,0.0002039671,0.000415136,0.03638534],"genre_scores_gemma":[0.9873874,0.0009499998,0.007759953,0.0001734841,0.00001274713,0.00003835841,0.0001379269,0.00001727482,0.00352296],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003744352,"threshold_uncertainty_score":0.01252615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02566844254398309,"score_gpt":0.2320008054034552,"score_spread":0.2063323628594722,"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."}}