{"id":"W4387578351","doi":"10.26434/chemrxiv-2023-cdrxf","title":"Introducing SpectraFit: An Open-Source Tool for Interactive Spectral Analysis.","year":2023,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Max-Planck-Gesellschaft","keywords":"Computer science; Software; Process (computing); Consistency (knowledge bases); Interface (matter); Data mining; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006931103,0.0004956239,0.0008944944,0.0002851492,0.0001715268,0.0003118796,0.001190944,0.0003549999,0.00006835511],"category_scores_gemma":[0.0004165486,0.0004966374,0.0005132462,0.0003724132,0.00008491551,0.000009695425,0.002374135,0.0004252772,0.00001734212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007283319,"about_ca_system_score_gemma":0.000119744,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000100505,"about_ca_topic_score_gemma":0.0002674851,"domain_scores_codex":[0.9970714,0.00006915376,0.0004888585,0.001660955,0.0001600217,0.0005496247],"domain_scores_gemma":[0.9979044,0.00004937572,0.0003506156,0.001377616,0.0001959363,0.0001221256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009367713,0.0006216652,0.00468288,0.0003034439,0.01584548,0.00001328853,0.0007300704,0.006844622,0.9398808,0.001701957,0.02610428,0.002334702],"study_design_scores_gemma":[0.002235667,0.001186899,0.01948635,0.00008231586,0.004011768,0.00001005062,0.0007133,0.004030749,0.8559682,0.007697069,0.1017913,0.00278633],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9619057,0.0006390091,0.03307359,0.0007227635,0.00115311,0.001262231,0.0001148596,0.00009652269,0.001032189],"genre_scores_gemma":[0.9710058,0.0007162732,0.01503539,0.0002407692,0.00277906,0.0004592021,0.002895161,0.0001536104,0.006714711],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08391261,"threshold_uncertainty_score":0.9997485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02626060105092668,"score_gpt":0.3111514323011202,"score_spread":0.2848908312501935,"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."}}