{"id":"W4406713780","doi":"10.1093/bioadv/vbae209","title":"<u>Imp</u>utation for <u>Li</u>pidomics and <u>Met</u>abolomics (ImpLiMet): a web-based application for optimization and method selection for missing data imputation","year":2024,"lang":"en","type":"article","venue":"Bioinformatics Advances","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Occupational Cancer Research Centre; University of Toronto; McGill Genome Centre; National Research Council Canada; McGill University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Missing data; Computer science; Mathematics; Statistics","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":[0.001476152,0.000231058,0.0003316127,0.0001940658,0.0002898017,0.0003354374,0.000136115,0.0001411732,0.00000165183],"category_scores_gemma":[0.002283406,0.0002119607,0.0000524977,0.000237874,0.00006227684,0.0009175297,0.00003935856,0.00007628775,3.611298e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006107143,"about_ca_system_score_gemma":0.0001490244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002565956,"about_ca_topic_score_gemma":0.000007178225,"domain_scores_codex":[0.9984791,0.00004567083,0.0006849645,0.0003890332,0.0001395135,0.0002617026],"domain_scores_gemma":[0.9931763,0.005926565,0.0003312178,0.0002219699,0.0002597127,0.00008427875],"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":[0.00013576,0.00002597838,0.00001974267,0.003515848,0.00003993365,3.419875e-8,0.0002061684,0.002738657,0.0004124019,0.193789,0.0002251773,0.7988912],"study_design_scores_gemma":[0.0007282381,0.0001893462,0.000004484781,0.0000869578,0.0001767808,0.000005528139,0.0001049118,0.6744938,0.0006671151,0.3198528,0.003508948,0.0001810162],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001703743,0.0004724339,0.9950651,0.0002882147,0.0001988351,0.002517578,0.001111414,0.0001510676,0.00002499192],"genre_scores_gemma":[0.001595748,0.0001426518,0.9966095,0.0001043424,0.0001286708,0.0005600781,0.0008074139,0.00004453904,0.000007023883],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7987102,"threshold_uncertainty_score":0.8643506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05619849722513385,"score_gpt":0.4230035011006127,"score_spread":0.3668050038754789,"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."}}