{"id":"W3137240878","doi":"10.1007/s12011-021-02666-6","title":"Speciation of Serum Copper and Zinc-Binding High- and Low-Molecular Mass Ligands in Dairy Cows Using HPLC-ICP-MS Technique","year":2021,"lang":"en","type":"article","venue":"Biological Trace Element Research","topic":"Trace Elements in Health","field":"Nursing","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Nutrition International","funders":"Russian Science Foundation; Ural Branch, Russian Academy of Sciences","keywords":"Zinc; Chemistry; Ceruloplasmin; Copper; Molecular mass; Albumin; Chromatography; Mass spectrometry; High-performance liquid chromatography; Genetic algorithm; Inductively coupled plasma mass spectrometry; Fractionation; Nuclear chemistry; Biochemistry; Biology; Organic chemistry; Enzyme","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003563539,0.0002053868,0.0004058187,0.0003040392,0.0001958051,0.00007564994,0.000181908,0.0002949371,0.0002019833],"category_scores_gemma":[0.0005176631,0.0001813444,0.00004226991,0.000699634,0.0002616679,0.0001247508,0.0002571567,0.0007090324,0.000003071129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003883259,"about_ca_system_score_gemma":0.00009450995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008085638,"about_ca_topic_score_gemma":0.00005930594,"domain_scores_codex":[0.9964357,0.0007768493,0.000638518,0.0006750243,0.000655105,0.000818825],"domain_scores_gemma":[0.9987062,0.000502996,0.0001308193,0.000297937,0.0001990523,0.0001630304],"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":[0.0001672594,0.0002405847,0.2030123,0.0002181205,0.00001834753,0.00007241763,0.0001415688,0.00001399574,0.7863402,0.001467279,0.00006227128,0.00824567],"study_design_scores_gemma":[0.001446293,0.0009070765,0.1698936,0.0004065488,0.00001128087,0.00001819552,0.0009744348,0.0002938481,0.8231304,0.001470789,0.00116693,0.0002805645],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953228,0.0008825711,0.0002765151,0.001938102,0.0001428456,0.001108402,0.00005173467,0.00003606521,0.000240945],"genre_scores_gemma":[0.9883672,0.0004384116,0.01085979,0.00006386692,0.0001067507,0.00006390322,0.00002718228,0.00002265204,0.00005022593],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03679029,"threshold_uncertainty_score":0.739501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1054094186657318,"score_gpt":0.4077516986174544,"score_spread":0.3023422799517226,"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."}}