{"id":"W2793784779","doi":"10.1093/bioinformatics/bty046","title":"pymzML v2.0: introducing a highly compressed and seekable gzip format","year":2018,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":90,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Jewish General Hospital","funders":"","keywords":"Computer science; Random access; Scripting language; File format; Documentation; Code (set theory); Source code; Scheme (mathematics); Field (mathematics); MIT License; Data file; Data compression; Algorithm; Software; Computational science; Computer engineering; Database; Programming language; Set (abstract data type)","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":[0.002586661,0.002268215,0.001214555,0.003208088,0.001384848,0.002730708,0.004109424,0.001257412,0.05557166],"category_scores_gemma":[0.01557546,0.001405053,0.001341666,0.00365763,0.001129137,0.003421088,0.004717299,0.003694084,0.05446129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001114946,"about_ca_system_score_gemma":0.002004441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002086729,"about_ca_topic_score_gemma":0.001689411,"domain_scores_codex":[0.9978997,0.0003530995,0.0002492555,0.00040722,0.0008136223,0.0002771599],"domain_scores_gemma":[0.9957706,0.001297493,0.0003523273,0.00119202,0.001072755,0.0003147306],"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":[0.001667153,0.0001571181,0.002812034,0.001552347,0.0001504459,0.0006950818,0.0006778729,0.004162794,0.03073213,0.01489038,0.7859536,0.1565491],"study_design_scores_gemma":[0.0004440977,0.0001709407,0.004014869,0.0005363113,0.00009371448,0.0008423708,0.0002195034,0.04639741,0.1204498,0.03646672,0.7899707,0.0003935553],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.006920279,0.0004012519,0.2640205,0.0009296236,0.0004975255,0.0004289683,0.04652307,0.672303,0.007975727],"genre_scores_gemma":[0.0526028,0.0007220872,0.40285,0.001792692,0.0003829931,0.003545603,0.1577166,0.3648424,0.01554479],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.05557166,"threshold_uncertainty_score":0.1859057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008613553688783167,"score_gpt":0.2295192498196013,"score_spread":0.2209056961308182,"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."}}