{"id":"W4393888490","doi":"10.5281/zenodo.8111839","title":"Public Data files for MassFormer","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Data file; Computer science; Database","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002939461,0.003820808,0.003076468,0.00348116,0.001650265,0.003741327,0.005331328,0.002170755,0.4577855],"category_scores_gemma":[0.01050459,0.001725987,0.00198128,0.005950423,0.0005537096,0.003398758,0.002558413,0.003101281,0.4165919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001701552,"about_ca_system_score_gemma":0.002862677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006500576,"about_ca_topic_score_gemma":0.01227745,"domain_scores_codex":[0.9982127,0.000258507,0.0001697215,0.0004735799,0.0007168285,0.0001686806],"domain_scores_gemma":[0.9966071,0.001060064,0.0002614954,0.0009493763,0.0008584053,0.0002636084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002898609,0.0000575853,0.0006149299,0.001055814,0.00009296611,0.0000503236,0.00002701871,0.001191987,0.001734104,0.00105258,0.9860311,0.007801754],"study_design_scores_gemma":[0.0004424338,0.0001050732,0.001862929,0.0001938333,0.0001137111,0.0001662045,0.0000471226,0.003142744,0.008132801,0.006565648,0.9791325,0.00009498822],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004605222,0.0003316026,0.004936564,0.0002139744,0.0001235552,0.00009953477,0.964314,0.02435962,0.005160731],"genre_scores_gemma":[0.001440336,0.0001997048,0.006407774,0.0003409873,0.0000352234,0.0004516975,0.9783357,0.009107904,0.003680652],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4577855,"threshold_uncertainty_score":0.7734032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1107927852962678,"score_gpt":0.2936778363083312,"score_spread":0.1828850510120633,"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."}}