{"id":"W2549240013","doi":"10.1016/j.copbio.2016.11.001","title":"Supporting metabolomics with adaptable software: design architectures for the end-user","year":2016,"lang":"en","type":"review","venue":"Current Opinion in Biotechnology","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Alberta Ingenuity; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada Foundation for Innovation; University of Calgary","keywords":"Workflow; Computer science; Profiling (computer programming); Software; Reuse; Software engineering; Software development; Data science; Coding (social sciences); Database; Operating system; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.00153898,0.001354724,0.00130138,0.001238104,0.0001398865,0.001769294,0.002809178,0.001794473,0.002850044],"category_scores_gemma":[0.00228083,0.0004467283,0.0008135329,0.001490466,0.0006263494,0.002712522,0.001506021,0.00215653,0.00272725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004146217,"about_ca_system_score_gemma":0.0008915649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006192676,"about_ca_topic_score_gemma":0.0006793717,"domain_scores_codex":[0.9993796,0.0000829336,0.00005172878,0.000120061,0.0003250678,0.00004056558],"domain_scores_gemma":[0.9984518,0.0008477378,0.000125644,0.0001708958,0.0003081975,0.00009567208],"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":[0.0000708481,0.00005663481,0.0003867092,0.004058702,0.00009019329,0.0001076523,0.00007615185,0.001511339,0.01283942,0.009555782,0.01063833,0.9606083],"study_design_scores_gemma":[0.00004662104,0.0001448242,0.001106697,0.002360335,0.0002429845,0.001063316,0.00006828027,0.00630108,0.01678777,0.01624287,0.9555332,0.0001020562],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.003732935,0.7839761,0.1936812,0.003024847,0.001326501,0.00008770816,0.0003698333,0.0030514,0.01074954],"genre_scores_gemma":[0.01773993,0.7884021,0.1793467,0.002930215,0.001439321,0.0001869609,0.001252792,0.0005830579,0.008118971],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002850044,"threshold_uncertainty_score":0.009534359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06261891200570759,"score_gpt":0.3637745446298202,"score_spread":0.3011556326241126,"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."}}