{"id":"W177729326","doi":"10.22215/etd/2003-05543","title":"Imputation of missing values by integrating artificial neural networks and case-based reasoning","year":2003,"lang":"en","type":"dissertation","venue":"","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Missing data; Imputation (statistics); Semantic reasoner; Computer science; Artificial intelligence; Matching (statistics); Data mining; Machine learning; Statistics; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003340508,0.0002271154,0.000274554,0.0001012072,0.0001874408,0.0002983944,0.0001787235,0.0002178811,0.000006482178],"category_scores_gemma":[0.00009397102,0.0002126881,0.00005810153,0.0002301202,0.00002715604,0.0002167959,0.00001492385,0.0003009726,3.371016e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002117369,"about_ca_system_score_gemma":0.00009732799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004045558,"about_ca_topic_score_gemma":0.0000875642,"domain_scores_codex":[0.9986203,0.0001257674,0.0004353789,0.0004178281,0.0001839913,0.0002167276],"domain_scores_gemma":[0.9990769,0.0001476808,0.0003173183,0.0001988887,0.0001820722,0.00007713111],"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":[0.00002338699,0.00006215831,0.00009258284,0.0001764282,0.00003218973,0.0001205975,0.001512432,0.0243722,0.003023894,0.01692272,0.0006247807,0.9530366],"study_design_scores_gemma":[0.00006858076,0.00005855077,0.000008360344,0.0001825473,0.00002013932,0.00006904414,0.0004296759,0.9923518,0.004572931,0.002022314,0.000001793292,0.000214206],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07981335,0.0005577463,0.9184638,0.00003845387,0.000335656,0.00009056475,0.000001664731,0.0000824142,0.0006163936],"genre_scores_gemma":[0.8990818,0.000005036932,0.1004622,0.00009196415,0.00003524242,0.000005863092,0.0001117403,0.00001794071,0.0001882519],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9679797,"threshold_uncertainty_score":0.8673168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01812135507120988,"score_gpt":0.2812449091939564,"score_spread":0.2631235541227465,"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."}}