{"id":"W2791530712","doi":"10.4155/bio-2018-0020","title":"Bioanalytical Techniques in Lipidomics","year":2018,"lang":"en","type":"article","venue":"Bioanalysis","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Lipidomics; Bioanalysis; Biochemical engineering; Chemistry; Nanotechnology; Computational biology; Data science; Chromatography; Computer science; Biology; Materials science; Engineering; Biochemistry","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":[0.004286175,0.001663479,0.001343259,0.004865533,0.001974712,0.00244386,0.002698652,0.00211223,0.003100531],"category_scores_gemma":[0.003734599,0.001347609,0.0006909497,0.003945664,0.003408965,0.003497722,0.002661652,0.004976208,0.004958244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001017995,"about_ca_system_score_gemma":0.001702793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006437963,"about_ca_topic_score_gemma":0.0007707727,"domain_scores_codex":[0.9968414,0.001501513,0.0002091248,0.000431102,0.0008697353,0.0001470208],"domain_scores_gemma":[0.9979572,0.000838958,0.0001675796,0.0004501035,0.0004671538,0.0001189546],"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":[0.0002353284,0.0002906513,0.0007388946,0.001760188,0.00007700681,0.0005557921,0.0004263849,0.0006642502,0.7719365,0.06896228,0.004950826,0.1494018],"study_design_scores_gemma":[0.0000360135,0.0002369104,0.001588511,0.0003591474,0.00007797396,0.002406985,0.0002452869,0.003490477,0.7246187,0.06556774,0.2012574,0.0001148981],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009645893,0.1016832,0.8699124,0.003316189,0.001643095,0.000286637,0.0003698719,0.0009635448,0.01217913],"genre_scores_gemma":[0.093022,0.1335336,0.736838,0.003204485,0.001802102,0.001095671,0.0009701743,0.000815485,0.02871856],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004865533,"threshold_uncertainty_score":0.02266771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008776781583058089,"score_gpt":0.2676986165530379,"score_spread":0.2589218349699798,"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."}}