{"id":"W6926687465","doi":"10.25384/sage.20069681","title":"sj-docx-1-cjk-10.1177_20543581221103100 – Supplemental material for Visuospatial and Executive Dysfunction in Patients With Acute Kidney Injury, Chronic Kidney Disease, and Kidney Failure: A Multilevel Modeling Analysis","year":2022,"lang":"en","type":"article","venue":"Sage Journals Data","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Kidney disease; Kidney; Executive dysfunction; Multilevel model; Executive summary","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001786832,0.001499421,0.001406192,0.003697872,0.001220231,0.003237908,0.002839782,0.001957552,0.8803874],"category_scores_gemma":[0.02560758,0.001523224,0.001526337,0.004071462,0.000385818,0.002471507,0.002009902,0.002290884,0.363584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001270313,"about_ca_system_score_gemma":0.002983806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02022337,"about_ca_topic_score_gemma":0.03221536,"domain_scores_codex":[0.99899,0.0001586552,0.0001638524,0.0001933125,0.0003371086,0.0001569831],"domain_scores_gemma":[0.9815795,0.01133399,0.001077139,0.001178425,0.003892059,0.000938881],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001225714,0.00008278283,0.00152583,0.0006119148,0.00002926389,0.00003175844,0.00004352002,0.0001526516,0.0001107269,0.0003986417,0.9911637,0.005726647],"study_design_scores_gemma":[0.002952461,0.0002979165,0.04875588,0.002552526,0.0002611116,0.0005617801,0.0008899536,0.003130421,0.002161155,0.01052004,0.9276446,0.0002722126],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005915627,0.00005158946,0.0009878096,0.0004418076,0.0001727652,0.0001862255,0.9917319,0.002095214,0.003741213],"genre_scores_gemma":[0.01126837,0.0003012069,0.01154316,0.001276145,0.0003854924,0.002714432,0.9278202,0.00647632,0.03821458],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8803874,"threshold_uncertainty_score":0.1706128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01499830949131111,"score_gpt":0.2709993716685701,"score_spread":0.256001062177259,"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."}}