{"id":"W4378650496","doi":"10.21203/rs.3.rs-2984141/v1","title":"Glucose trend prediction model based on improved Wavelet Transform and Gated Recurrent Unit","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Diabetes Management and Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"123 Certification (Canada)","funders":"","keywords":"Mean squared error; Smoothing; Wavelet transform; Noise reduction; Computer science; Discrete wavelet transform; Pattern recognition (psychology); Wavelet; Algorithm; Artificial intelligence; Mathematics; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059467,0.0005526174,0.001003634,0.0003374017,0.0002570667,0.0006665908,0.001025934,0.0007790903,0.002227844],"category_scores_gemma":[0.001538199,0.0003494624,0.0007045279,0.0006492093,0.0002142717,0.001061082,0.0003992066,0.00106683,0.0005269892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003626891,"about_ca_system_score_gemma":0.0007594994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00939721,"about_ca_topic_score_gemma":0.007161585,"domain_scores_codex":[0.9997674,0.00003337015,0.00001630213,0.00009678781,0.00004722728,0.00003890779],"domain_scores_gemma":[0.9996868,0.0001372011,0.00003174645,0.00002398209,0.0001026243,0.00001767189],"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":[0.000301447,0.0001471794,0.003122808,0.00009537718,0.0001528378,0.0001736996,0.00005483296,0.8305479,0.006933983,0.007453579,0.002799427,0.1482168],"study_design_scores_gemma":[0.000002545739,0.000007723886,0.0001484865,0.000001000596,0.000008865036,0.00000628886,8.703014e-7,0.9992199,0.0001598644,0.0004032045,0.00003925604,0.000001989188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1111221,0.0006982337,0.884357,0.0004676686,0.0002413287,0.00002819765,0.0003587826,0.0007728861,0.001953904],"genre_scores_gemma":[0.9436879,0.0005987448,0.04878595,0.0001038722,0.0001195073,0.00007383055,0.0007150663,0.0000684554,0.005846752],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00939721,"threshold_uncertainty_score":0.01868504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1127682431333147,"score_gpt":0.4018623938636003,"score_spread":0.2890941507302855,"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."}}