{"id":"W1524239195","doi":"","title":"Regional Variety Trials: Reducing Information Asymmetries in the Western Canadian CWRS Wheat Industry","year":2012,"lang":"en","type":"article","venue":"University Library - University of Saskatchewan (University of Saskatchewan)","topic":"Horticultural and Viticultural Research","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Variety (cybernetics); Business; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01124011,0.0004585598,0.0009217897,0.0007784124,0.00191774,0.001635303,0.002074801,0.0008938535,0.006188296],"category_scores_gemma":[0.02342122,0.0002781789,0.0004347534,0.001581319,0.001097442,0.001081351,0.001020498,0.0008932822,0.0003758337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01000437,"about_ca_system_score_gemma":0.01738742,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5164005,"about_ca_topic_score_gemma":0.7629972,"domain_scores_codex":[0.994357,0.003701719,0.0001517451,0.0007274072,0.0006704658,0.0003916915],"domain_scores_gemma":[0.9794101,0.01209074,0.002491665,0.001830516,0.002411469,0.001765503],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.1001667,0.01610699,0.09712125,0.001463909,0.001517772,0.001009499,0.008338282,0.04553065,0.03568184,0.01600346,0.02219629,0.6548633],"study_design_scores_gemma":[0.03243873,0.07627102,0.6525249,0.0007070088,0.005475014,0.0003596349,0.02497665,0.09070361,0.02845134,0.0196628,0.06772958,0.0006998142],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9817659,0.0005630238,0.004260866,0.0007422253,0.00004450116,0.0006763361,0.0003164039,0.0001335776,0.01149723],"genre_scores_gemma":[0.9896611,0.0002247526,0.005501295,0.0002809812,0.00001786273,0.0002212082,0.0002276217,0.00002329357,0.003841962],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4835995,"threshold_uncertainty_score":0.972895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03422763216309033,"score_gpt":0.2083119523304886,"score_spread":0.1740843201673983,"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."}}