{"id":"W2060564963","doi":"10.1016/j.tvjl.2014.09.014","title":"Measurement of serum immunoglobulin G in dairy cattle using Fourier-transform infrared spectroscopy: A reagent free approach","year":2014,"lang":"en","type":"article","venue":"The Veterinary Journal","topic":"Animal health and immunology","field":"Veterinary","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Prince Edward Island","funders":"Atlantic Canada Opportunities Agency; Ministère de l'Education Nationale, de l'Enseignement Superieur et de la Recherche; Ministry of Higher Education; Ministry of Higher Education and Scientific Research","keywords":"Fourier transform infrared spectroscopy; Spectroscopy; Analytical Chemistry (journal); Chemistry; Radial immunodiffusion; Partial least squares regression; Calibration; Fourier transform; Mathematics; Chromatography; Antibody; Statistics; Immunology; Biology; Optics; Physics","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":[0.001397095,0.0005412607,0.0004541373,0.0009451552,0.0003633853,0.0006199731,0.0006918273,0.001227413,0.0003369626],"category_scores_gemma":[0.0007988655,0.000367289,0.0003446397,0.0006251256,0.0007644508,0.0005023885,0.0003796288,0.001001038,0.0001860396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003094565,"about_ca_system_score_gemma":0.0004259995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00161422,"about_ca_topic_score_gemma":0.002745748,"domain_scores_codex":[0.9986618,0.0004462433,0.00005061588,0.0001897628,0.0005452848,0.000106424],"domain_scores_gemma":[0.9995895,0.000144734,0.00008242496,0.00004083298,0.0001021497,0.00004030414],"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":[0.0007787823,0.0001535431,0.01193389,0.0001328994,0.00005143344,0.00005245498,0.0001121005,0.0001138345,0.9757078,0.00008055782,0.00007607912,0.01080654],"study_design_scores_gemma":[0.00009503457,0.002802837,0.09443309,0.00004171231,0.0002968733,0.00117974,0.0003239406,0.003558918,0.8947806,0.0002775362,0.002148008,0.00006168314],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9569421,0.003028931,0.03790728,0.0001577348,0.0000834303,0.0001034793,0.0002673984,0.0001315096,0.001378245],"genre_scores_gemma":[0.9367501,0.002855436,0.05712287,0.0004251685,0.00007224366,0.0001445256,0.0004236177,0.00003420173,0.002171922],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00161422,"threshold_uncertainty_score":0.007388592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1032357887654242,"score_gpt":0.3305061655909576,"score_spread":0.2272703768255335,"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."}}