{"id":"W1630974822","doi":"10.22004/ag.econ.158288","title":"Ex Ante Economic Impact Analysis of Novel Traits in Canola","year":2013,"lang":"en","type":"article","venue":"AgEcon Search (University of Minnesota, USA)","topic":"Agricultural Innovations and Practices","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Canola; Ex-ante; Economic impact analysis; Economics; Agricultural economics; Natural resource economics; Business; Agronomy; Biology; Microeconomics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001878849,0.0004788534,0.0004719725,0.0008392144,0.0004297489,0.001239225,0.0006542587,0.0005213768,0.002265465],"category_scores_gemma":[0.003743996,0.0003090173,0.0005836347,0.0007909943,0.0006436252,0.001038936,0.0007106792,0.0005924843,0.0001062848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004978309,"about_ca_system_score_gemma":0.002320069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08086702,"about_ca_topic_score_gemma":0.07703833,"domain_scores_codex":[0.9995564,0.0001575693,0.00001192343,0.00005309514,0.00009339074,0.000127661],"domain_scores_gemma":[0.9981682,0.001222108,0.0002003174,0.0001074725,0.0002091804,0.00009268401],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000140545,0.00005545641,0.01048654,0.00002316404,0.00005597468,0.00008990595,0.00001605584,0.9752632,0.001160978,0.008851577,0.0001940067,0.003662601],"study_design_scores_gemma":[0.00001777015,0.0001054089,0.01142473,0.000004621707,0.00005463719,0.00001876492,0.00007089572,0.9830748,0.0006101762,0.004010289,0.0005918993,0.00001600039],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9839102,0.0002016266,0.008875347,0.0003451914,0.000008328484,0.00003646204,0.0003852893,0.00003531192,0.006202245],"genre_scores_gemma":[0.9970048,0.0001054167,0.0009963451,0.0000241456,0.000003573708,0.00001161191,0.0001736581,0.000005491161,0.001674967],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08086702,"threshold_uncertainty_score":0.1607926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04644357518396063,"score_gpt":0.2565500048408269,"score_spread":0.2101064296568663,"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."}}