{"id":"W2986340550","doi":"10.1093/jhered/esz065","title":"Predicting Adaptive Genetic Variation of Loblolly Pine (Pinus taeda L.) Populations Under Projected Future Climates Based on Multivariate Models","year":2019,"lang":"en","type":"article","venue":"Journal of Heredity","topic":"Forest ecology and management","field":"Environmental Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Institute of Food and Agriculture","keywords":"Loblolly pine; Pinus <genus>; Biology; Multivariate statistics; Genetic variation; Variation (astronomy); Multivariate analysis; Tree breeding; Woody plant; Ecology; Botany; Statistics; Genetics; Mathematics; Gene","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":[0.0006323806,0.000235572,0.0001792444,0.0003830945,0.0002281081,0.000361363,0.0002635158,0.000155137,0.0002958606],"category_scores_gemma":[0.001115412,0.0001053312,0.0004031267,0.0003303687,0.0002007969,0.0002688766,0.000216223,0.0002460554,0.00005036239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003380281,"about_ca_system_score_gemma":0.0002612013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0107719,"about_ca_topic_score_gemma":0.01802847,"domain_scores_codex":[0.9998449,0.00005981014,0.000005811868,0.00006454848,0.00001058084,0.00001425406],"domain_scores_gemma":[0.999602,0.0002203723,0.00008588048,0.00003423728,0.00002734738,0.00003021452],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001380495,0.00009553403,0.6792706,0.00002934199,0.000261557,0.0001161442,0.0002639494,0.28929,0.007252088,0.0009651983,0.0003553605,0.02196215],"study_design_scores_gemma":[0.000007469857,0.00003750126,0.2430267,0.000006707108,0.0000447421,0.00004783835,0.000134831,0.7546118,0.000461852,0.00142066,0.000185817,0.00001411373],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922001,0.00003984107,0.007474669,0.00003122825,0.000001534955,0.000002607227,0.000118838,0.00002332751,0.0001078248],"genre_scores_gemma":[0.99729,0.0000341882,0.002365944,0.000007328046,0.000002534319,0.000005275667,0.0002057519,0.000005973379,0.0000830019],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0107719,"threshold_uncertainty_score":0.02141839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01957812664916913,"score_gpt":0.2400863935051272,"score_spread":0.2205082668559581,"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."}}