{"id":"W4388235557","doi":"10.1109/sampta59647.2023.10301413","title":"Data Imputation with an Autoencoder and MAGIC","year":2023,"lang":"en","type":"article","venue":"","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Imputation (statistics); Missing data; Autoencoder; Computer science; Robustness (evolution); Mean squared error; Artificial intelligence; Deep learning; Data mining; Machine learning; Pattern recognition (psychology); Statistics; Mathematics","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":[0.004889357,0.001046669,0.002183715,0.001245395,0.000850539,0.001013685,0.00360708,0.00219244,0.002055722],"category_scores_gemma":[0.01278531,0.0009900281,0.001578759,0.00191395,0.001102572,0.00291664,0.002790758,0.003686546,0.00110502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007172488,"about_ca_system_score_gemma":0.001896782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004131197,"about_ca_topic_score_gemma":0.006636802,"domain_scores_codex":[0.9976609,0.0008160678,0.0001660629,0.0007330786,0.0004786714,0.0001452898],"domain_scores_gemma":[0.9951223,0.00184914,0.0004040543,0.001430326,0.001036433,0.0001577624],"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":[0.0003317908,0.0001749174,0.006312321,0.000195567,0.0005381117,0.0002556266,0.0002353458,0.4139363,0.003510479,0.0250416,0.01122708,0.5382409],"study_design_scores_gemma":[0.00001401171,0.00004275235,0.0005185113,0.0000211312,0.00002906748,0.0001045097,0.000017661,0.9781718,0.00169351,0.01736882,0.001994428,0.00002375733],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004611197,0.0002571039,0.993519,0.0001926808,0.00005931259,0.00002193662,0.0001080949,0.0008546056,0.0003759218],"genre_scores_gemma":[0.2219775,0.0004617325,0.7706912,0.0006096023,0.0002216573,0.000197144,0.001678688,0.0003087216,0.003853689],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004889357,"threshold_uncertainty_score":0.02585769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06830957920597121,"score_gpt":0.309401058408185,"score_spread":0.2410914792022138,"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."}}