{"id":"W2764144586","doi":"10.1017/s1751731117002506","title":"Targeted metabolomics: new insights into pathobiology of retained placenta in dairy cows and potential risk biomarkers","year":2017,"lang":"en","type":"article","venue":"animal","topic":"Reproductive Physiology in Livestock","field":"Agricultural and Biological Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Genome Alberta; Natural Sciences and Engineering Research Council of Canada; Alberta Livestock and Meat Agency","keywords":"Metabolomics; Retained placenta; Dairy cattle; Placenta; Dairy industry; Biology; Bioinformatics; Biotechnology; Computational biology; Food science; Pregnancy; Animal science; Fetus; Genetics","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":[0.0002837069,0.0003656941,0.0003166602,0.0007475113,0.0001195465,0.0004414195,0.0001564577,0.000367869,0.0004361414],"category_scores_gemma":[0.0001914724,0.0001481834,0.0001946603,0.0005943176,0.0001552521,0.0003137104,0.0003284086,0.0002583372,0.00008126615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002422855,"about_ca_system_score_gemma":0.0002119108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006995078,"about_ca_topic_score_gemma":0.0009446461,"domain_scores_codex":[0.9998955,0.00002938036,0.000004717478,0.00003410945,0.00002044787,0.00001573388],"domain_scores_gemma":[0.9999065,0.00002069257,0.00004120926,0.000007253459,0.00001196678,0.00001237843],"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":[0.0009193728,0.00005183401,0.02515079,0.0002403129,0.0001022504,0.0001715192,0.0001017079,0.0004786345,0.9447751,0.0001646593,0.000103196,0.02774058],"study_design_scores_gemma":[0.00004950031,0.001910528,0.6344382,0.00007754261,0.0003878747,0.002064139,0.0005169446,0.01332508,0.3381189,0.001949948,0.007083807,0.00007750543],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9646478,0.01058444,0.02219329,0.0002498343,0.00002178523,0.00004129697,0.001371999,0.00008844627,0.0008011266],"genre_scores_gemma":[0.9780748,0.004147531,0.0157969,0.00021642,0.0000332756,0.00005514944,0.0007527694,0.00001406907,0.0009090721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007475113,"threshold_uncertainty_score":0.001757979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01445941780458977,"score_gpt":0.2328758333120252,"score_spread":0.2184164155074354,"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."}}