{"id":"W4387585496","doi":"10.51219/jaimld/sebastian-ifeanyi-obeta/01","title":"A Comparative study of Long Short-Term Memory and Gated Recurrent Unit","year":2023,"lang":"en","type":"article","venue":"Journal of Artificial Intelligence Machine Learning and Data Science","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Term (time); Unit (ring theory); Short-term memory; Computer science; Psychology; Neuroscience; Working memory; Physics; Cognition; Mathematics education","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":[],"consensus_categories":[],"category_scores_codex":[0.003217641,0.0001186885,0.0002924057,0.0005322998,0.0003707938,0.0002672839,0.001359807,0.00002445966,0.000003062274],"category_scores_gemma":[0.0004234166,0.00009562397,0.00001844957,0.001616062,0.0003392814,0.0009205031,0.001086111,0.0003562983,0.00000213828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001127686,"about_ca_system_score_gemma":0.0001074657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004073077,"about_ca_topic_score_gemma":0.00002699473,"domain_scores_codex":[0.9981445,0.0001902112,0.0005783646,0.0003738759,0.0005063936,0.0002066449],"domain_scores_gemma":[0.9985917,0.0002344038,0.0003556046,0.0003482912,0.0003395717,0.0001304547],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001430113,0.0007718207,0.05449467,0.00005517648,0.00006784703,0.0001539543,0.02726929,0.07049809,0.004763991,0.002152642,0.0001146806,0.8395148],"study_design_scores_gemma":[0.00004464314,0.00096467,0.005863861,0.00007814758,0.00001184415,0.00006349959,0.001788688,0.9870943,0.00359812,0.0003398539,0.00002918946,0.0001232304],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6821647,0.0001922634,0.3171855,0.0001005934,0.0001439856,0.00009527709,0.000002148297,0.00006294843,0.00005266232],"genre_scores_gemma":[0.989449,0.0002445166,0.01025222,0.00000728737,0.00002773878,4.509321e-7,0.000002993819,0.000003388819,0.00001235831],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9165962,"threshold_uncertainty_score":0.3899432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.139188697223615,"score_gpt":0.4124876882296603,"score_spread":0.2732989910060452,"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."}}