{"id":"W2995293713","doi":"10.1139/cjb-2019-0082","title":"Amino acid composition, protein content and accurate nitrogen-to-protein conversion factor for sheepgrass (<i>Leymus chinensis</i>)","year":2019,"lang":"en","type":"article","venue":"Botany","topic":"Ruminant Nutrition and Digestive Physiology","field":"Agricultural and Biological Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick; Agriculture and Agri-Food Canada","funders":"Science and Technology Major Project of Inner Mongolia; Chinese Academy of Sciences","keywords":"Kjeldahl method; Leymus; Nitrogen; Conversion factor; Ammonium; Non-protein nitrogen; Biology; Amino acid; Botany; Composition (language); Ammonia; Food science; Chemistry; Biochemistry; Agronomy; Organic chemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.00006924898,0.0001679587,0.0002521552,0.00001417635,0.000164119,0.00004957504,0.0001258276,0.00008966369,0.0001681309],"category_scores_gemma":[0.00003361246,0.00007275133,0.00008497165,0.0001176911,0.00004943694,0.000110871,0.00006455448,0.00006976963,0.0001199996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002133785,"about_ca_system_score_gemma":0.000005088636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004258611,"about_ca_topic_score_gemma":0.00002062942,"domain_scores_codex":[0.9989873,0.00005781997,0.0002044338,0.0003587559,0.0001152097,0.0002764614],"domain_scores_gemma":[0.9994934,0.00006944824,0.00009105262,0.00005975545,0.0001336108,0.0001527171],"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":[0.0002518126,0.00007406511,0.005051031,0.00001475998,0.000009242582,0.000001111421,0.00001925737,1.589241e-7,0.991705,0.000370974,0.0001976618,0.002304953],"study_design_scores_gemma":[0.001025434,0.001432489,0.4488463,0.00008430182,0.000009624853,0.000006405613,0.0001755874,0.00008178576,0.5366092,0.0008551031,0.01051753,0.00035616],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947869,0.0001412078,0.00002921166,0.002878916,0.00008493468,0.001680289,0.0002664121,0.00005783493,0.0000742565],"genre_scores_gemma":[0.9985296,0.000007814934,0.0002338221,0.0007193455,0.00009049004,0.0001114952,0.00003992456,0.000001858274,0.0002657076],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4550957,"threshold_uncertainty_score":0.2966713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02744349488362046,"score_gpt":0.2262918045583053,"score_spread":0.1988483096746848,"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."}}