{"id":"W2913675559","doi":"10.1111/eva.12773","title":"Linking genotype to phenotype to identify genetic variation relating to host susceptibility in the mountain pine beetle system","year":2019,"lang":"en","type":"article","venue":"Evolutionary Applications","topic":"Forest Insect Ecology and Management","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biology; Candidate gene; Mountain pine beetle; Population; Pinus contorta; Genetics; Genetic variation; Population genetics; Allele; Phenotype; Evolutionary biology; Ecology; Gene","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005702563,0.0001037024,0.00009448509,0.00008089465,0.000272647,0.00002200974,0.0003998213,0.00006012362,0.0004396573],"category_scores_gemma":[0.00003486639,0.00009789781,0.00002631901,0.0009375124,0.00002390642,0.00009868889,0.0002757701,0.0001176779,0.01053816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006905353,"about_ca_system_score_gemma":0.00001639864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008043011,"about_ca_topic_score_gemma":0.001288079,"domain_scores_codex":[0.9987332,0.00009886699,0.0002684621,0.000422771,0.0002321106,0.0002446162],"domain_scores_gemma":[0.9992174,0.00008780191,0.00005491962,0.0005475927,0.0000180358,0.00007427667],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006685115,0.000382874,0.4822269,0.00007710427,0.00002102768,0.000003062636,0.00483563,0.3906802,0.06018224,0.0543388,0.00479052,0.002394743],"study_design_scores_gemma":[0.00008593301,0.00007029085,0.9857515,0.00001200286,0.000008691894,0.000002460709,0.0002317347,0.0023344,0.000007455791,0.001047366,0.01033301,0.0001151342],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9333388,0.00002086316,0.05464248,0.001346749,0.0001252218,0.003105508,0.00001164731,0.00006306499,0.007345628],"genre_scores_gemma":[0.9861794,9.830054e-7,0.0112948,0.0009390548,0.00006937382,0.0009794042,0.00002464672,0.00001054055,0.0005017798],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5035246,"threshold_uncertainty_score":0.9902322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007617490095608877,"score_gpt":0.2426737053747542,"score_spread":0.2350562152791453,"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."}}