{"id":"W7065017813","doi":"","title":"Detecting and Imputing Hidden Missing Values in Time Series Data : Case study: Alfa Laval","year":2024,"lang":"en","type":"article","venue":"Hogskolan Ihalmstad (Halmstad University)","topic":"Astrophysical Phenomena and Observations","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Missing data; Imputation (statistics); Time series; Series (stratigraphy); Interpolation (computer graphics); Identification (biology)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002233143,0.0006382077,0.0004960307,0.001257888,0.001289971,0.001267002,0.00207643,0.001418692,0.0007523725],"category_scores_gemma":[0.006776786,0.0001679987,0.0006567508,0.00251853,0.0009465967,0.001270612,0.000902432,0.001178021,0.0003536011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001850652,"about_ca_system_score_gemma":0.001589485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1129189,"about_ca_topic_score_gemma":0.1382057,"domain_scores_codex":[0.998719,0.0003006892,0.0001120773,0.0002771989,0.0004067941,0.0001843228],"domain_scores_gemma":[0.9957001,0.001866452,0.0004008288,0.0007559489,0.00100899,0.0002676275],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002108466,0.001890164,0.499537,0.001007279,0.0006636959,0.01938577,0.004457286,0.1387542,0.008732933,0.007484998,0.09739213,0.2185862],"study_design_scores_gemma":[0.0004724856,0.0007754271,0.3688,0.0003093823,0.0002877313,0.00263815,0.01075795,0.491235,0.02103728,0.00839199,0.09502503,0.0002695898],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9785814,0.000455702,0.004951012,0.002621642,0.00009929646,0.0001129409,0.008503776,0.0008230156,0.003851317],"genre_scores_gemma":[0.972043,0.0002981366,0.01298103,0.0002757979,0.00009179056,0.00009679116,0.01229772,0.00007184051,0.001843977],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.1129189,"threshold_uncertainty_score":0.2245233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02105125876847465,"score_gpt":0.2420539003841781,"score_spread":0.2210026416157035,"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."}}