{"id":"W2189458455","doi":"10.1515/sg-2006-0011","title":"Accuracy of Ranking Individuals in Field Tests of Different Designs: A Computer Simulation","year":2006,"lang":"en","type":"article","venue":"Silvae genetica/Silvae Genetica","topic":"Forest ecology and management","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Plant Biotechnology Institute; Government of British Columbia","funders":"","keywords":"Heritability; Statistics; Ranking (information retrieval); Trait; Tree (set theory); Biology; Mathematics; Population; Variance (accounting); Computer science; Artificial intelligence; Evolutionary biology; Demography","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":[0.01235106,0.0004284775,0.0008456599,0.000659503,0.0003963855,0.0007584341,0.0009320288,0.0006972413,0.0009238317],"category_scores_gemma":[0.0346579,0.0003376094,0.0005285618,0.0005947166,0.0007628738,0.0006423618,0.0003574254,0.0005675463,0.0001392332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001893506,"about_ca_system_score_gemma":0.001015163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0105966,"about_ca_topic_score_gemma":0.007723363,"domain_scores_codex":[0.9959122,0.00286977,0.0001976509,0.000383128,0.0003818708,0.0002553445],"domain_scores_gemma":[0.8953338,0.09247064,0.003039458,0.004951071,0.003595309,0.0006097787],"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":[0.001111581,0.0003013467,0.02570809,0.00005383829,0.0001166531,0.00004865173,0.0001024885,0.9542661,0.001956695,0.0009626056,0.0002012008,0.01517066],"study_design_scores_gemma":[0.0001883182,0.000954082,0.01159554,0.00001598364,0.00004983343,0.00004837835,0.00005477032,0.9829191,0.002811146,0.001079084,0.0002490783,0.00003468674],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9848296,0.00007114014,0.01369209,0.00004387225,0.00000656115,0.00008563032,0.0001371777,0.0001075613,0.001026465],"genre_scores_gemma":[0.9864141,0.00002391045,0.01299376,0.00001662936,0.000002111293,0.000088852,0.0001776197,0.00001139084,0.0002716671],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01235106,"threshold_uncertainty_score":0.06531936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01204265095730547,"score_gpt":0.2474918962189876,"score_spread":0.2354492452616821,"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."}}