{"id":"W4283382967","doi":"10.3389/fvets.2022.887163","title":"Suitability of Dried Blood Spots for Accelerating Veterinary Biobank Collections and Identifying Metabolomics Biomarkers With Minimal Resources","year":2022,"lang":"en","type":"article","venue":"Frontiers in Veterinary Science","topic":"Biosimilars and Bioanalytical Methods","field":"Immunology and Microbiology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Mars Petcare","keywords":"Biobank; Dried blood; Medicine; Veterinary medicine; Biology; Bioinformatics; Chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00545892,0.0008780437,0.0007191792,0.001441712,0.0005419339,0.001809414,0.001179145,0.00122407,0.004530193],"category_scores_gemma":[0.006949483,0.000644156,0.0005569453,0.001094144,0.0008473651,0.0008033227,0.0007844674,0.0008604635,0.00357827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002857246,"about_ca_system_score_gemma":0.0005742881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005621591,"about_ca_topic_score_gemma":0.001507,"domain_scores_codex":[0.995641,0.001526409,0.0003303642,0.0008394713,0.001480962,0.0001818129],"domain_scores_gemma":[0.997218,0.0007760206,0.0004179073,0.0004571951,0.0009593585,0.0001715995],"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":[0.001263479,0.0003373919,0.01113541,0.0008463472,0.0001846021,0.0004957517,0.0002763594,0.0007587176,0.9035896,0.001019761,0.006056629,0.07403596],"study_design_scores_gemma":[0.0002604576,0.002558092,0.06765089,0.0004916093,0.0004294375,0.00531279,0.0006530522,0.008030658,0.8317441,0.00288927,0.0798278,0.0001518065],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3514768,0.01013108,0.5970889,0.005190735,0.001426291,0.006497323,0.0117735,0.005503489,0.01091196],"genre_scores_gemma":[0.3512746,0.006207292,0.6156327,0.002368269,0.0005902395,0.00459157,0.01163087,0.0005409876,0.007163536],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00545892,"threshold_uncertainty_score":0.02886987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04813269396272362,"score_gpt":0.3005118165231641,"score_spread":0.2523791225604405,"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."}}