{"id":"W3151552372","doi":"10.3233/jpd-202476","title":"Lipidomics Prediction of Parkinson’s Disease Severity: A Machine-Learning Analysis","year":2021,"lang":"en","type":"article","venue":"Journal of Parkinson s Disease","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke","keywords":"Lipidome; Lipidomics; Parkinson's disease; Biomarker; Disease; Sphingolipid; Globotriaosylceramide; Internal medicine; Medicine; Biology; Bioinformatics; Biochemistry; Fabry disease","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":[0.0003968949,0.0001954724,0.0004809117,0.0002363383,0.00009894789,0.00003651314,0.0001802674,0.00006980593,0.00008650556],"category_scores_gemma":[0.0007296061,0.0001798796,0.0007237077,0.0004970366,0.00007034078,0.00001318951,0.0001399894,0.0001970488,0.00000135987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003244523,"about_ca_system_score_gemma":0.0003099114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006743627,"about_ca_topic_score_gemma":0.00001608509,"domain_scores_codex":[0.998293,0.0002105701,0.0006044031,0.0003018453,0.0003651773,0.0002250036],"domain_scores_gemma":[0.9981536,0.00002484795,0.0006095606,0.0003284463,0.0004334228,0.0004500663],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001679339,0.0005900462,0.9406337,0.0001146449,0.003095282,0.0001737862,0.0000608209,0.001680188,0.04823498,0.0000875595,0.002051341,0.001598297],"study_design_scores_gemma":[0.001120824,0.0001592735,0.6191898,0.00003058638,0.002662612,0.00001338308,0.000118135,0.001959917,0.00611087,0.0001653576,0.3682658,0.0002033925],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9783388,0.01751807,0.002803901,0.0003917836,0.0003994567,0.00007311854,0.0003316997,0.000006299237,0.0001368986],"genre_scores_gemma":[0.9873921,0.01049329,0.0009387985,0.0001514819,0.0004847908,0.000004776758,0.0001478865,0.00002042778,0.000366412],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3662145,"threshold_uncertainty_score":0.7335278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01029674566318791,"score_gpt":0.2398967267372856,"score_spread":0.2295999810740977,"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."}}