{"id":"W3123111512","doi":"","title":"Economic Analysis of Marker-Assisted Selection in Canola","year":2011,"lang":"en","type":"article","venue":"2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania","topic":"Nitrogen and Sulfur Effects on Brassica","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Canola; Selection (genetic algorithm); Marker-assisted selection; Business; Computer science; Biology; Agronomy; Genetic marker; Artificial intelligence; Genetics","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":[0.005079671,0.000368231,0.0008271616,0.001914351,0.0004932609,0.001436266,0.0008502777,0.0006134851,0.002424848],"category_scores_gemma":[0.01265308,0.0003103541,0.000692319,0.001835961,0.0008759713,0.0007820436,0.0005464387,0.0006444124,0.0001065942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002902218,"about_ca_system_score_gemma":0.001231677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007061602,"about_ca_topic_score_gemma":0.006179124,"domain_scores_codex":[0.9987424,0.0009132939,0.00002778734,0.00007816746,0.0001445304,0.00009382994],"domain_scores_gemma":[0.9892141,0.01003956,0.000256549,0.0001487563,0.0002297314,0.0001112549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008534582,0.0002614055,0.02695586,0.0001371334,0.0003107649,0.0005081502,0.0001138833,0.8224674,0.004806592,0.09867326,0.0009061232,0.04400596],"study_design_scores_gemma":[0.0000536058,0.0001756944,0.02121802,0.00001466455,0.0001186536,0.00007600052,0.0001177482,0.9534512,0.0008011722,0.02297037,0.000975212,0.00002757996],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9002601,0.001527333,0.08602562,0.001259076,0.00004772434,0.0001276688,0.0003394276,0.0000982542,0.01031477],"genre_scores_gemma":[0.9890614,0.000385143,0.007839243,0.00005327866,0.00002060322,0.00004624835,0.0001336514,0.00001449128,0.002445992],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007061602,"threshold_uncertainty_score":0.02686417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009978599558687693,"score_gpt":0.2318305581121046,"score_spread":0.2218519585534169,"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."}}