{"id":"W2150270381","doi":"10.4141/cjas-2014-184","title":"Effect of post-weaning residual feed intake classification on grazed grass intake and performance in pregnant beef heifers","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Animal Science","topic":"Ruminant Nutrition and Digestive Physiology","field":"Agricultural and Biological Sciences","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Agriculture and Agri-Food Canada; Agriculture Food and Rural Development; University of Alberta","funders":"Agriculture and Agri-Food Canada; Alberta Livestock and Meat Agency; University of Alberta; Alberta Beef Producers; University of Manitoba; Manitoba Rural Adaptation Council","keywords":"Residual feed intake; Pasture; Animal science; Beef cattle; Forage; Weaning; Crossbreed; Biology; Grazing; Feed conversion ratio; Agronomy; Body weight","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001073518,0.0000857142,0.0001773735,0.000112518,0.0001329113,0.00004109173,0.0002550031,0.00004309771,0.000008194485],"category_scores_gemma":[0.0003832895,0.00003663799,0.00002744312,0.0005032248,0.0004613207,0.0002903446,0.00001494391,0.0001389386,0.000002181957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001020171,"about_ca_system_score_gemma":0.0002184075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001520401,"about_ca_topic_score_gemma":0.005314293,"domain_scores_codex":[0.9990371,0.0001011913,0.0002402635,0.0001578665,0.0002078965,0.0002556729],"domain_scores_gemma":[0.9990281,0.000111344,0.0001748372,0.00002996687,0.0002224458,0.0004332696],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0005780779,0.00002194165,0.1307685,0.000008368402,0.000001857087,0.00001403045,0.0002145555,0.000005386422,0.8502154,0.000452604,0.00005474763,0.01766452],"study_design_scores_gemma":[0.0002951816,0.008568316,0.9774203,0.0001438096,0.000003401402,0.00003677162,0.0004630504,0.00007237989,0.01270243,0.00004884741,0.0001718495,0.00007372081],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983155,0.0001003756,1.815058e-7,0.001076979,0.00007451309,0.00009257065,0.000006870664,0.000002394202,0.0003306889],"genre_scores_gemma":[0.9998213,0.00002264839,0.00002012405,0.00008028786,0.0000479583,0.000001233004,0.000002244989,5.718816e-7,0.000003606162],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8466517,"threshold_uncertainty_score":0.29655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03390645934016875,"score_gpt":0.2487939149626681,"score_spread":0.2148874556224993,"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."}}