{"id":"W4389391506","doi":"10.3390/f14122382","title":"Will Genomic Information Facilitate Forest Tree Breeding for Disease and Pest Resistance?","year":2023,"lang":"en","type":"article","venue":"Forests","topic":"Forest Insect Ecology and Management","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Canadian Forest Service","funders":"U.S. Department of Agriculture","keywords":"Resistance (ecology); Biology; Threatened species; Genomics; Tree breeding; Biotechnology; Selection (genetic algorithm); Agroforestry; Environmental resource management; Ecology; Genome; Genetics; Habitat; Computer science; Gene; Woody plant","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":[0.0002163892,0.0001054258,0.00008664665,0.00006900947,0.0002242021,0.00003569918,0.0001288783,0.00003860562,0.00009687047],"category_scores_gemma":[0.00006996988,0.0001002374,0.00003917764,0.0001651289,0.0001335731,0.0008129516,0.0001724681,0.00004342415,0.0005876994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000802722,"about_ca_system_score_gemma":0.00000712379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004245383,"about_ca_topic_score_gemma":0.01240863,"domain_scores_codex":[0.9992411,0.00001047495,0.0001636287,0.0001744925,0.0001157028,0.0002945709],"domain_scores_gemma":[0.9996155,0.0000600381,0.00005241697,0.0001502514,0.000005857942,0.0001159437],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004047472,0.00003535708,0.8249933,0.0002298411,0.00003294543,0.0000177626,0.001505992,0.006603895,0.0001716671,0.01575426,0.1384001,0.01185007],"study_design_scores_gemma":[0.0003839582,0.00005732167,0.8548717,0.000007992351,0.00001209893,6.306208e-7,0.00005158361,0.004206046,0.00000204052,0.02103894,0.1192569,0.0001108291],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934691,0.00001977256,0.001797416,0.0005555179,0.0001777495,0.0006163621,0.00006129489,0.000115513,0.003187262],"genre_scores_gemma":[0.9951998,0.00002818456,0.0002659773,0.0001911408,0.00002799803,0.0001910054,0.0001147681,0.000008611702,0.003972521],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02987833,"threshold_uncertainty_score":0.7553882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01226054595313013,"score_gpt":0.2098830463070153,"score_spread":0.1976225003538852,"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."}}