{"id":"W2027635134","doi":"10.2135/cropsci2011.01.0016","title":"Assessing the Representativeness and Repeatability of Test Locations for Genotype Evaluation","year":2011,"lang":"en","type":"article","venue":"Crop Science","topic":"Genetics and Plant Breeding","field":"Agricultural and Biological Sciences","cited_by":100,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Representativeness heuristic; Repeatability; Biplot; Biology; Selection (genetic algorithm); Genotype; Gene–environment interaction; Statistics; Adaptation (eye); Biotechnology; Computer science; Genetics; Mathematics; Machine learning","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":[0.006876401,0.0004435873,0.0005708481,0.002625119,0.0005171711,0.0008424774,0.0005712751,0.0003796158,0.0009410026],"category_scores_gemma":[0.01743913,0.0001935639,0.0004685368,0.001562526,0.0005076705,0.0004671325,0.0005342102,0.0004602362,0.0003407994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000573398,"about_ca_system_score_gemma":0.0004746293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005375017,"about_ca_topic_score_gemma":0.01377048,"domain_scores_codex":[0.995116,0.002088886,0.000533391,0.0006496019,0.001387851,0.000224296],"domain_scores_gemma":[0.9750131,0.01026666,0.004523227,0.003879932,0.005731674,0.0005854084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001801269,0.0003781076,0.6218968,0.0003390876,0.0006332732,0.0004395835,0.001486635,0.01645646,0.1921342,0.0007541528,0.001336833,0.1623436],"study_design_scores_gemma":[0.00002930406,0.000827312,0.9236057,0.00002689594,0.0001286969,0.0003586519,0.0004927592,0.02374735,0.04857601,0.0003685027,0.001745608,0.00009331533],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9205322,0.0001782236,0.07592628,0.00002428129,0.0000267219,0.0002219611,0.0009184651,0.0006666649,0.001505227],"genre_scores_gemma":[0.9561241,0.00003171515,0.04260689,0.00001098097,0.000005410223,0.0001376208,0.0006120275,0.00007542341,0.000395876],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006876401,"threshold_uncertainty_score":0.03636628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2349254148040905,"score_gpt":0.354014364705616,"score_spread":0.1190889499015255,"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."}}