{"id":"W2594216924","doi":"10.2135/cropsci2016.10.0885","title":"Past and Future Use of Wild Relatives in Crop Breeding","year":2017,"lang":"en","type":"article","venue":"Crop Science","topic":"Genetic and Environmental Crop Studies","field":"Agricultural and Biological Sciences","cited_by":610,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of British Columbia","funders":"","keywords":"Crop; Agriculture; Crop diversity; Biology; Threatened species; Genetic resources; Agroforestry; Resource (disambiguation); Biotechnology; Plant breeding; Environmental resource management; Agronomy; Ecology; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001564458,0.00006266793,0.00008795466,0.000008710616,0.0006432181,0.0001195356,0.0002514688,0.00002470034,0.00002396778],"category_scores_gemma":[0.00004656238,0.00002322276,0.0000150533,0.00009914782,0.001508147,0.000330687,0.0002809616,0.00004924527,0.000003008998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009726247,"about_ca_system_score_gemma":0.000002588432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000224471,"about_ca_topic_score_gemma":0.0001362706,"domain_scores_codex":[0.9993859,0.000007924534,0.00008955807,0.0002086445,0.0001447397,0.0001632323],"domain_scores_gemma":[0.9997782,0.00002578506,0.0000730573,0.00006271854,0.00001401785,0.00004622141],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000004262709,0.0000138804,0.6125328,0.00000183178,8.13429e-7,0.000001159311,0.000282528,0.000002656861,0.3556637,0.0001525625,0.00003179054,0.03131201],"study_design_scores_gemma":[0.0000443387,0.00007049145,0.9938687,0.00001298673,0.000001367339,0.000001688013,0.0005685807,0.00001768679,0.002233033,0.000102823,0.003017144,0.00006114602],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973981,0.0001840473,5.123439e-7,0.001287355,0.00007619175,0.00004965154,0.000004009023,0.000003918846,0.0009961959],"genre_scores_gemma":[0.9993222,0.0001907978,0.0002133298,0.00002698285,0.00007606151,0.000001402853,2.631657e-7,2.482526e-7,0.0001687191],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3813359,"threshold_uncertainty_score":0.5556831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04194243402814135,"score_gpt":0.2345284121651487,"score_spread":0.1925859781370074,"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."}}