{"id":"W2052571285","doi":"10.1016/j.biortech.2006.07.010","title":"Zeolite (clinoptilolite) as feed additive to reduce manure mineral content","year":2006,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Animal Nutrition and Physiology","field":"Agricultural and Biological Sciences","cited_by":41,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Zeolite; Clinoptilolite; Chemistry; Particle size; Pellets; Adsorption; Manure; Mineralogy; Materials science; Agronomy; Organic chemistry; Composite material","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":[0.00008479665,0.0002388972,0.000243861,0.0001855216,0.0001103192,0.0002130776,0.0001974864,0.0002756373,0.0007527579],"category_scores_gemma":[0.00009308422,0.0000854408,0.0002625117,0.0001716048,0.00008357945,0.0001287494,0.000136347,0.0001917281,0.0001525939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001634638,"about_ca_system_score_gemma":0.0002298006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001421338,"about_ca_topic_score_gemma":0.002913961,"domain_scores_codex":[0.9999208,0.00001290279,0.000006289348,0.0000122112,0.00002349287,0.00002418571],"domain_scores_gemma":[0.9999533,0.000007560343,0.00001271889,0.000003167904,0.0000103287,0.00001292332],"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":[0.0002626321,0.00003508678,0.000149566,0.00004556234,0.000009136467,0.00003225023,0.000004407943,0.0000928521,0.9971607,0.00002537799,0.00002950436,0.002152928],"study_design_scores_gemma":[0.00001416771,0.0002778244,0.001401579,0.00000392633,0.00002323894,0.0000347094,0.00001191829,0.0003698092,0.9972784,0.000009195312,0.000573008,0.000002341822],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969519,0.0007485264,0.001350606,0.00005475133,0.00002402676,0.00001477413,0.00008655721,0.00005271081,0.0007160577],"genre_scores_gemma":[0.9959384,0.0004947828,0.001463955,0.00002716615,0.000004406013,0.000007144999,0.0000868199,0.000007302966,0.001970038],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001421338,"threshold_uncertainty_score":0.002826095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02077288944571287,"score_gpt":0.2275364809590309,"score_spread":0.206763591513318,"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."}}