{"id":"W6928857201","doi":"10.4224/23001959","title":"Metabolomics profiling of wheat resistance","year":2016,"lang":"en","type":"article","venue":"NPARC","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metabolomics; Profiling (computer programming); Plant disease resistance; Resistance (ecology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005790184,0.0005314322,0.0003458071,0.0008554999,0.0001747328,0.0006075015,0.0002963917,0.0005451282,0.001076859],"category_scores_gemma":[0.0003777155,0.0002279435,0.0003288152,0.0008521383,0.0001212207,0.0004539166,0.0004717291,0.0006840481,0.001032143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004357327,"about_ca_system_score_gemma":0.0002906163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001308567,"about_ca_topic_score_gemma":0.002950484,"domain_scores_codex":[0.9997618,0.00004904364,0.00001279848,0.00006061501,0.00008498439,0.00003089464],"domain_scores_gemma":[0.9998299,0.00003504842,0.00004737007,0.00001517427,0.00005193602,0.00002061857],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0000544079,0.00003758517,0.00461892,0.0001259501,0.00002422517,0.00001937256,0.0000222499,0.0002039441,0.9732208,0.0002638806,0.0002809664,0.02112758],"study_design_scores_gemma":[0.00003450173,0.0003858135,0.1156016,0.00004198457,0.00006507102,0.0002277687,0.0001391855,0.01002331,0.8514297,0.002189474,0.01982223,0.00003943898],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6890379,0.01593645,0.2596742,0.002952234,0.0001923628,0.0007101848,0.01765542,0.001214734,0.01262656],"genre_scores_gemma":[0.6995316,0.01016688,0.2681379,0.001402767,0.00008460474,0.0004916328,0.01066051,0.0001316365,0.009392484],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001308567,"threshold_uncertainty_score":0.003602386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01235028539944667,"score_gpt":0.2525273851527445,"score_spread":0.2401770997532979,"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."}}