{"id":"W1985279331","doi":"10.2135/cropsci2004.0161","title":"Responses to Divergent Phenotypic Selection for Fiber Traits in Timothy","year":2005,"lang":"en","type":"article","venue":"Crop Science","topic":"Ruminant Nutrition and Digestive Physiology","field":"Agricultural and Biological Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; McGill University","funders":"","keywords":"Neutral Detergent Fiber; Biology; Population; Biomass (ecology); Forage; Lignin; Fiber; Phenotypic trait; Animal science; Selection (genetic algorithm); Agronomy; Cellulose; Botany; Phenotype; Chemistry; Biochemistry; Medicine","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003704973,0.0003488124,0.0002382917,0.000326251,0.0002408169,0.0003771659,0.0002237764,0.0002317534,0.000689155],"category_scores_gemma":[0.0004828541,0.0001322158,0.000179512,0.0001665992,0.0002420477,0.0001127678,0.0003595744,0.0003596368,0.0001343133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004551716,"about_ca_system_score_gemma":0.0001917278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001314323,"about_ca_topic_score_gemma":0.003122741,"domain_scores_codex":[0.9997458,0.00007434085,0.00001917025,0.00006482097,0.00006040901,0.00003540917],"domain_scores_gemma":[0.9995989,0.0001032056,0.0001051529,0.0000298696,0.0000516122,0.0001113304],"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":[0.0002463066,0.00003676141,0.008432509,0.00001332256,0.0000211453,0.00006644366,0.00009317129,0.00007436109,0.9889001,0.00002957059,0.00001206436,0.002074263],"study_design_scores_gemma":[0.00008094939,0.001768427,0.8193204,0.00001271432,0.0001377899,0.000957471,0.0005678893,0.003577513,0.1717446,0.000168691,0.001613568,0.00005004203],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996926,0.00002987727,0.0001141439,0.000006073866,9.72168e-7,0.000001647973,0.00002695849,0.000002971366,0.000124853],"genre_scores_gemma":[0.9982393,0.00005732848,0.0006414212,0.00005589658,0.000005206316,0.00001224634,0.0002680966,0.00001592697,0.000704547],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001314323,"threshold_uncertainty_score":0.003302515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03316728055329143,"score_gpt":0.2778119340547212,"score_spread":0.2446446535014298,"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."}}