{"id":"W4220684188","doi":"10.1016/j.psj.2022.101866","title":"Feather pulp: a novel substrate useful for proton nuclear magnetic resonance spectroscopy metabolomics and biomarker discovery","year":2022,"lang":"en","type":"article","venue":"Poultry Science","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; University of Lethbridge","funders":"Canadian Glycomics Network; Alberta Agriculture and Forestry; University of Lethbridge; Agriculture and Agri-Food Canada; Lethbridge Research and Development Centre; Canadian Poultry Research Council","keywords":"Feather; Metabolome; Metabolomics; Pulp (tooth); Metabolite; Broiler; Repeatability; Food science; Biology; Chemistry; Chromatography; Biochemistry; Pathology; Ecology; Medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003205396,0.0007187497,0.0003442902,0.0004268747,0.0002491791,0.000656865,0.0002756415,0.0007150233,0.0008942658],"category_scores_gemma":[0.0003172616,0.0003021133,0.0002398046,0.0003285407,0.0002526457,0.0005520181,0.0003551832,0.0005216709,0.000522078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001422448,"about_ca_system_score_gemma":0.0001517895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004331087,"about_ca_topic_score_gemma":0.001218349,"domain_scores_codex":[0.9997849,0.00005162013,0.00001368857,0.00007753364,0.00004644236,0.00002575343],"domain_scores_gemma":[0.9998367,0.00004635154,0.00003853743,0.00001652178,0.00003334335,0.00002848795],"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":[0.00009079465,0.00001296831,0.0003593079,0.00007353462,0.00000825644,0.00008278465,0.0000109376,0.00004721347,0.9958681,0.00005187081,0.00004336756,0.003350853],"study_design_scores_gemma":[0.00001755263,0.0004235323,0.01067425,0.00004656841,0.00007126329,0.0008874575,0.00008466608,0.00211114,0.9771513,0.0001807344,0.008321161,0.00003031724],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8854669,0.01915165,0.08875925,0.0004430751,0.0003031514,0.0001918597,0.001403276,0.0002800114,0.004000749],"genre_scores_gemma":[0.8971848,0.006805379,0.08846383,0.0002979817,0.0001008454,0.000118034,0.001465705,0.00008880845,0.005474626],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008942658,"threshold_uncertainty_score":0.002991676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01661361825631952,"score_gpt":0.25634092030254,"score_spread":0.2397273020462205,"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."}}