{"id":"W2000081597","doi":"10.1007/s11306-010-0231-x","title":"Metabolomics in pesticide research and development: review and future perspectives","year":2010,"lang":"en","type":"article","venue":"Metabolomics","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":124,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Metabolomics; Biotechnology; Agrochemical; Biochemical engineering; Pharmacogenomics; Functional genomics; Biology; Computational biology; Genomics; Risk analysis (engineering); Agriculture; Pharmacology; Bioinformatics; Engineering; Ecology; Medicine","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":[0.001458526,0.0002467514,0.0004821997,0.0001873478,0.0001953303,0.00004754866,0.0002094601,0.0001911468,0.00004431042],"category_scores_gemma":[0.0003892918,0.0002190617,0.000035752,0.000263219,0.0003402009,0.00001060343,0.0003778309,0.0005551013,0.000005866603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001063036,"about_ca_system_score_gemma":0.0001096987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001124991,"about_ca_topic_score_gemma":0.0001851148,"domain_scores_codex":[0.9983134,0.0001059654,0.0003269405,0.0006370469,0.0001651967,0.0004514386],"domain_scores_gemma":[0.9991754,0.00004308613,0.00007753696,0.0003697092,0.0002033215,0.0001309075],"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":[0.0002878802,0.0006063048,0.04842063,0.0009227068,0.0006804154,0.00002238895,0.0023032,0.000001087808,0.7720875,0.1099698,0.003786692,0.0609114],"study_design_scores_gemma":[0.0008825885,0.0001127606,0.07815611,0.0000248195,0.00008498299,0.00006341651,0.001418639,0.00000632774,0.02231235,0.0007611021,0.8956986,0.0004782884],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.785583,0.2114901,0.00004227974,0.001368657,0.0001870479,0.0003329659,0.00001281243,0.000009501843,0.000973577],"genre_scores_gemma":[0.5112433,0.4590971,0.02754662,0.0005834686,0.0007276615,0.0001087319,0.00004929323,0.00005872759,0.0005850362],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8919119,"threshold_uncertainty_score":0.8933077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02305719507654507,"score_gpt":0.3104849673378048,"score_spread":0.2874277722612597,"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."}}