{"id":"W4386085939","doi":"10.21203/rs.3.rs-3286368/v1","title":"OpenMS 3 expands the frontiers of open-source computational mass spectrometry","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Horizon 2020 Framework Programme; Deutsche Forschungsgemeinschaft; European Commission; Genome Canada; Ontario Genomics; Government of Canada; Wellcome Trust; German Network for Bioinformatics Infrastructure; Ontario Genomics Institute","keywords":"Mass spectrometry; Open source; Computer science; Chemistry; Chromatography; Operating system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.006738281,0.002857217,0.002138569,0.002218043,0.001579084,0.007555746,0.00676191,0.003173132,0.03735193],"category_scores_gemma":[0.01785273,0.00122501,0.003713324,0.002100118,0.001826333,0.008243315,0.009637606,0.004557446,0.01611147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001372258,"about_ca_system_score_gemma":0.003954468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003726084,"about_ca_topic_score_gemma":0.00410197,"domain_scores_codex":[0.9959794,0.0009022812,0.0001991304,0.0008507724,0.001800403,0.000267983],"domain_scores_gemma":[0.9871787,0.005903241,0.0003030534,0.004234419,0.001620228,0.0007603673],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.004362115,0.0014934,0.005631252,0.002719708,0.00208128,0.0009003354,0.0009216415,0.08989631,0.050514,0.198288,0.2632288,0.3799632],"study_design_scores_gemma":[0.0006220653,0.0001552305,0.001537606,0.0001996711,0.0002028564,0.0002754363,0.0001293777,0.4434401,0.03093407,0.2822683,0.2400312,0.0002040525],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.01574877,0.0008632584,0.7652764,0.003821191,0.001671115,0.0001851758,0.007495597,0.1800345,0.02490406],"genre_scores_gemma":[0.1210451,0.001155024,0.7691829,0.001916755,0.001297825,0.0005012543,0.03333605,0.05697453,0.01459055],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.9932381,"threshold_uncertainty_score":0.1249547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07022207637487096,"score_gpt":0.3954882475249942,"score_spread":0.3252661711501232,"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."}}