{"id":"W2565739830","doi":"10.1038/nchembio.2265","title":"Mapping an amazing thicket","year":2016,"lang":"en","type":"article","venue":"Nature Chemical Biology","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Natural (archaeology); Resource (disambiguation); Computational biology; Thicket; Data science; Natural resource; Nanotechnology; World Wide Web; Biology; Ecology; Materials science; Paleontology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001716745,0.0001660574,0.0002004281,0.0000489996,0.00005151414,0.00000755368,0.0002694512,0.0006769695,0.00005216501],"category_scores_gemma":[0.0003945015,0.0001033543,0.00008393735,0.00009250675,0.0001540287,0.000003076343,0.0001935871,0.0002225911,0.00001597173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001409621,"about_ca_system_score_gemma":0.00002250191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001725197,"about_ca_topic_score_gemma":0.000003179608,"domain_scores_codex":[0.9989107,0.00004721329,0.0001640162,0.0004853695,0.00005593141,0.0003368046],"domain_scores_gemma":[0.9994113,0.00003369774,0.00006078975,0.0003293191,0.0000720732,0.00009275551],"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":[0.00003366157,0.00002441013,0.002813906,0.000003413339,0.0000472479,8.913128e-7,0.000008451624,1.390014e-8,0.9842643,0.003139767,0.001443636,0.008220284],"study_design_scores_gemma":[0.0003779496,0.00009732848,0.0007532521,0.000005797958,0.000005338034,0.00001119885,0.00001733893,7.774332e-7,0.7777035,0.00218011,0.2186658,0.0001815606],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920364,0.002535658,0.001063803,0.001354998,0.0003280968,0.00007733676,0.00003253022,0.00003025142,0.002540903],"genre_scores_gemma":[0.9953321,0.0005131498,0.002009698,0.001075988,0.0007262172,0.00001196995,0.00008252922,0.00001611291,0.0002322785],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2172222,"threshold_uncertainty_score":0.5221409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008809055540812497,"score_gpt":0.2698074868302938,"score_spread":0.2609984312894813,"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."}}