{"id":"W3174706135","doi":"10.1096/fasebj.2018.32.1_supplement.475.2","title":"Seeing the invisible by NMR spectroscopy","year":2018,"lang":"en","type":"article","venue":"The FASEB Journal","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 Toronto","funders":"","keywords":"Complementarity (molecular biology); Nuclear magnetic resonance spectroscopy; Computer science; Chemistry; Nanotechnology; Physics; Nuclear magnetic resonance; Biology; Materials science; Genetics","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":[0.004454827,0.0006211936,0.0008758331,0.001004017,0.001980868,0.004063745,0.001123999,0.003876724,0.006061571],"category_scores_gemma":[0.004965278,0.000428767,0.0005036804,0.0005460113,0.007274649,0.01190356,0.004025809,0.008974951,0.003805488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001054174,"about_ca_system_score_gemma":0.0009515763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005216087,"about_ca_topic_score_gemma":0.0005712713,"domain_scores_codex":[0.9980764,0.0006702067,0.00005714899,0.0002512494,0.0008004288,0.0001445932],"domain_scores_gemma":[0.9978576,0.0008478355,0.0001261915,0.0003895694,0.0004307364,0.0003480333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003823806,0.0001659403,0.001450702,0.001826392,0.0001469443,0.001037019,0.002278783,0.0007589087,0.1168506,0.4622212,0.1511925,0.2616888],"study_design_scores_gemma":[0.00003219805,0.0001543091,0.0006326521,0.0006232351,0.0000390134,0.001297953,0.001068371,0.000776643,0.01679099,0.3072855,0.6711816,0.0001176157],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"methods","genre_scores_codex":[0.02108262,0.5054712,0.1422668,0.2063151,0.01977333,0.00007642473,0.0005507978,0.00153924,0.1029245],"genre_scores_gemma":[0.29629,0.4291507,0.1190222,0.07556236,0.02353077,0.0001969622,0.0004925059,0.0006212718,0.05513323],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.006061571,"threshold_uncertainty_score":0.02355963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009144892338499465,"score_gpt":0.2493509423264851,"score_spread":0.2402060499879856,"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."}}