{"id":"W3135631566","doi":"10.17504/protocols.io.smgec3w","title":"UPLC-MS/MS Detection v1","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Metabolomics; Fish <Actinopterygii>; Chromatography; Scale (ratio); Computational biology; Chemistry; Computer science; Biology; Fishery; Cartography; Geography","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":[],"consensus_categories":[],"category_scores_codex":[0.003065475,0.006000654,0.002966241,0.00517817,0.003845929,0.002096479,0.002368294,0.00379401,0.03302957],"category_scores_gemma":[0.004195624,0.001725295,0.001770181,0.002986385,0.001812101,0.002872029,0.002938518,0.004176044,0.01663914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001456682,"about_ca_system_score_gemma":0.005156559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003487085,"about_ca_topic_score_gemma":0.004769236,"domain_scores_codex":[0.9956086,0.0003691406,0.0002072283,0.001917482,0.001156438,0.0007410989],"domain_scores_gemma":[0.9980131,0.0005058589,0.0002673754,0.0002628195,0.000755985,0.0001948681],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001819133,0.0006699516,0.004509501,0.002101399,0.0005596742,0.001060294,0.0002783127,0.000913632,0.9108748,0.004906032,0.02722325,0.04508398],"study_design_scores_gemma":[0.0004920879,0.001433439,0.01925385,0.0003350292,0.0004694912,0.004658845,0.0002120771,0.01717873,0.8162404,0.00607157,0.1330448,0.0006097121],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.2894814,0.01803354,0.481484,0.004298416,0.003144003,0.006110608,0.07235246,0.05716874,0.06792693],"genre_scores_gemma":[0.3130897,0.008199007,0.507445,0.0118919,0.001108632,0.01228271,0.08219513,0.01200933,0.05177857],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.03302957,"threshold_uncertainty_score":0.110495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01266783129237438,"score_gpt":0.2557190532514634,"score_spread":0.243051221959089,"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."}}