{"id":"W4406375754","doi":"10.3390/agriculture15020167","title":"Interactions Between Trace Elements and Macro Minerals in Pregnant Heifers","year":2025,"lang":"en","type":"article","venue":"Agriculture","topic":"Selenium in Biological Systems","field":"Nursing","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakeland College; University of Guelph; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Trace Minerals; TRACE (psycholinguistics); Macro; Biology; Environmental science; Environmental chemistry; Chemistry; Animal science; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009317254,0.0001245109,0.0001905581,0.00004679911,0.00006581842,0.00004000134,0.0001066772,0.0001216233,0.00002824009],"category_scores_gemma":[0.0000689017,0.00007330701,0.0000368778,0.0002938384,0.00002191922,0.00008406275,0.000037921,0.0002117473,0.00001169435],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000822373,"about_ca_system_score_gemma":0.000003142659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002215507,"about_ca_topic_score_gemma":0.0002888294,"domain_scores_codex":[0.999113,0.00009515799,0.0002596345,0.0002470933,0.00007617875,0.0002089624],"domain_scores_gemma":[0.9996387,0.0001316369,0.00005944729,0.00009577772,0.00003200294,0.00004242566],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005194848,0.0001504518,0.557583,0.0001040687,0.00007756329,0.000004302956,0.0008051191,0.000009079762,0.347437,0.0002973677,0.07984112,0.01363901],"study_design_scores_gemma":[0.0005744669,0.00006491962,0.8343858,0.0004716659,0.00003955152,0.000006958883,0.0007122002,0.00001113261,0.01264283,0.0003416266,0.1505549,0.0001939678],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9892513,0.001119931,0.000007855871,0.004164579,0.0005454513,0.0004006391,0.00001787227,0.00005819757,0.004434132],"genre_scores_gemma":[0.9970124,0.0000178492,0.0001793824,0.0001987094,0.0001367228,0.0000389159,0.00003104516,0.000003553811,0.002381371],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3347942,"threshold_uncertainty_score":0.2989373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01630934200505788,"score_gpt":0.2881877927555523,"score_spread":0.2718784507504944,"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."}}