{"id":"W2127665473","doi":"10.1109/iembs.2008.4650170","title":"Imputation of missing values by integrating neural networks and case-based reasoning","year":2008,"lang":"en","type":"article","venue":"","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Children's Hospital of Eastern Ontario; Izaak Walton Killam Health Centre; University of Ottawa; Carleton University","funders":"University of British Columbia","keywords":"Imputation (statistics); Missing data; Computer science; Artificial neural network; Data mining; Artificial intelligence; Machine learning; Case-based reasoning","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003153754,0.000104102,0.000132299,0.00005465025,0.0003028921,0.00007437829,0.0001270224,0.0000496416,0.0000029536],"category_scores_gemma":[0.00007116402,0.00009046122,0.00002800621,0.000196985,0.00004845182,0.0002748319,0.00004129811,0.0001323967,2.519546e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000120997,"about_ca_system_score_gemma":0.00003540501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003519085,"about_ca_topic_score_gemma":0.000004100933,"domain_scores_codex":[0.9991831,0.00009038772,0.0002113836,0.0002194406,0.0001137611,0.0001819508],"domain_scores_gemma":[0.9992399,0.0003722195,0.0001225255,0.0001424627,0.00005742435,0.00006549145],"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":[0.00003601251,0.00008807466,0.07479025,0.0001248995,0.00004813962,0.001717131,0.008767245,0.3704771,0.002685429,0.003462313,0.007793485,0.5300099],"study_design_scores_gemma":[0.0001564942,0.00006832362,0.0002023922,0.00006452812,0.000003592892,0.0007399271,0.00006210831,0.997331,0.001127624,0.0001276402,0.00001121827,0.000105195],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1993379,0.0004538792,0.7995518,0.0001666293,0.00005280309,0.00004100124,5.957705e-7,0.0001041233,0.0002912502],"genre_scores_gemma":[0.8041995,0.000001745277,0.1955927,0.0001538842,0.00001809491,0.000001150637,0.000004498862,0.00000521235,0.00002319404],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6268538,"threshold_uncertainty_score":0.3688902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01427367791079696,"score_gpt":0.2392655763324815,"score_spread":0.2249918984216845,"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."}}