{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003210611,0.0001893861,0.0003314104,0.0002410758,0.0002761358,0.0003339585,0.000139923,0.0002229457,0.0004287517],"category_scores_gemma":[0.0005908177,0.0002670293,0.000132563,0.0001592646,0.0003490154,0.0001768581,0.0002110728,0.0002956883,0.00009474155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003258773,"about_ca_system_score_gemma":0.0003095893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006213617,"about_ca_topic_score_gemma":0.01578682,"domain_scores_codex":[0.9997675,0.0000894616,0.00001230715,0.00005022713,0.00004022204,0.00004034185],"domain_scores_gemma":[0.9996374,0.0001536343,0.0000954604,0.00001514446,0.00003357478,0.00006476833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00649762,0.0004036682,0.6594365,0.0001108477,0.0001658047,0.0009015219,0.001080711,0.0004191031,0.3125553,0.0001063556,0.00009868038,0.0182239],"study_design_scores_gemma":[0.00001600336,0.002449177,0.9819174,0.00000936653,0.0001081851,0.0003804065,0.000543677,0.0009540099,0.0130379,0.0000780209,0.000496332,0.000009423874],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996767,0.0001408688,0.00007958677,0.000006510241,6.088939e-7,0.000001219083,0.00001176061,0.000001263291,0.00008136695],"genre_scores_gemma":[0.9991279,0.0001386284,0.0002127027,0.00001915404,0.000001471772,0.000004255627,0.00004317635,0.000002269202,0.0004504354],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006213617,"threshold_uncertainty_score":0.01235485,"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."}}