{"id":"W2195900930","doi":"10.4141/cjps2013-228","title":"Benefits of mixing timothy with alfalfa for forage yield, nutritive value, and weed suppression in northern environments","year":2013,"lang":"en","type":"article","venue":"Canadian Journal of Plant Science","topic":"Ruminant Nutrition and Digestive Physiology","field":"Agricultural and Biological Sciences","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Agronomy; Forage; Monoculture; Weed; Seeding; Dry matter; Biology; Phleum; Cultivar; Yield (engineering); Legume; Medicago sativa; Sowing; Weed control","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":[0.0001819032,0.00006429749,0.0001368136,0.00006286237,0.0001289484,0.00002717951,0.0001744834,0.00003132857,0.00002495319],"category_scores_gemma":[0.00007042012,0.0000258694,0.00002123121,0.0001671581,0.000262098,0.0002595768,0.00001080119,0.00006012436,0.000001163179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002944899,"about_ca_system_score_gemma":0.00005877293,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004488415,"about_ca_topic_score_gemma":0.02600612,"domain_scores_codex":[0.9993634,0.00001604291,0.0001613386,0.0001218088,0.0001136492,0.0002237591],"domain_scores_gemma":[0.999391,0.0001452063,0.0001317278,0.00002071516,0.00006303727,0.0002482668],"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":[0.00008704495,0.00005788949,0.1622263,0.00001180212,0.000005026233,0.00001276513,0.0002410976,0.0001161604,0.8270201,0.0003706872,0.0002438071,0.009607311],"study_design_scores_gemma":[0.0003003553,0.000619695,0.9823448,0.0002154369,0.000003608117,0.00004982968,0.000487707,0.00007153005,0.01462793,0.0005016607,0.0006939102,0.00008353477],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988618,0.0001486083,0.000006820137,0.000541652,0.0000378779,0.0001964162,0.0001340575,6.752851e-7,0.00007201394],"genre_scores_gemma":[0.999694,0.00002232775,0.0001559594,0.00007491805,0.00002708861,0.00000551072,0.000006344498,4.759871e-7,0.00001340887],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8201185,"threshold_uncertainty_score":0.9917668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01553426828816542,"score_gpt":0.1890688923036929,"score_spread":0.1735346240155275,"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."}}