{"id":"W4312755295","doi":"10.1177/15353702221121602","title":"Evaluation methodology for deep learning imputation models","year":2022,"lang":"en","type":"article","venue":"Experimental Biology and Medicine","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; McMaster University; Vector Institute","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Imputation (statistics); Computer science; Mean squared error; Deep learning; Artificial intelligence; Missing data; Machine learning; Regression; Data mining; Pattern recognition (psychology); Statistics; Mathematics","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":[0.002860205,0.00007119437,0.0001866481,0.00004408531,0.0002342279,0.000001421743,0.00004193518,0.00003941967,0.00061959],"category_scores_gemma":[0.001867425,0.00005618973,0.00001615277,0.0000425357,0.000117065,0.00001837581,0.00005054687,0.0001068104,3.629242e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004134743,"about_ca_system_score_gemma":0.00001358003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001794418,"about_ca_topic_score_gemma":6.733216e-7,"domain_scores_codex":[0.9985042,0.0009279913,0.0001725776,0.0001771043,0.00009839657,0.0001197746],"domain_scores_gemma":[0.9978194,0.001967366,0.00007395802,0.00005219383,0.00005085319,0.00003621309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001161103,0.00004985037,0.00003141609,0.0000109819,0.00003459422,5.088674e-7,0.005126154,0.0000893665,0.07667668,0.7844291,0.0001499088,0.1332853],"study_design_scores_gemma":[0.001104814,0.001679536,0.00002748726,0.000003810788,0.00005545646,0.00001551964,0.00547269,0.1051297,0.003705352,0.8823221,0.0004132902,0.00007029994],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1107983,0.002785466,0.8839425,0.0003553015,0.000388367,0.0004333627,0.000006168345,0.0000294116,0.001261046],"genre_scores_gemma":[0.8138758,0.00001234225,0.1854077,0.0002106306,0.00007479882,0.0003326305,0.00003749275,0.000006129927,0.00004244154],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7030774,"threshold_uncertainty_score":0.6784077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3760736381918804,"score_gpt":0.5441129889542737,"score_spread":0.1680393507623933,"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."}}