{"id":"W2099307819","doi":"10.1111/j.1755-0998.2009.02717.x","title":"Characterization of microsatellite loci in the fungus, <i>Grosmannia clavigera</i>, a pine pathogen associated with the mountain pine beetle","year":2009,"lang":"en","type":"article","venue":"Molecular Ecology Resources","topic":"Forest Insect Ecology and Management","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; Natural Resources Canada; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Genome Alberta; Cabildo de Tenerife; Genome British Columbia","keywords":"Biology; Microsatellite; Mountain pine beetle; Fungus; Locus (genetics); Botany; Population; Bark beetle; PEST analysis; Gene flow; Allele; Ecology; Genetic variation; Genetics; Curculionidae; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000998028,0.0001392765,0.0001050653,0.0004759187,0.0002305091,0.0002593191,0.000150512,0.0001937655,0.0003213373],"category_scores_gemma":[0.000365429,0.00007931188,0.00009030208,0.0004108033,0.0001965318,0.00005834533,0.0001159124,0.0001526016,0.0001198777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003621583,"about_ca_system_score_gemma":0.00051536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0344127,"about_ca_topic_score_gemma":0.0892377,"domain_scores_codex":[0.9999005,0.000006937209,0.000007311266,0.00002693506,0.00003834807,0.00001995778],"domain_scores_gemma":[0.9996137,0.00004234277,0.000162498,0.00001890532,0.00009238462,0.00007020802],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002027208,0.00006708421,0.1562826,0.00007977409,0.00004387883,0.0002605569,0.0008006875,0.0002880174,0.824851,0.0001322598,0.000171452,0.01682],"study_design_scores_gemma":[0.00001621755,0.0001776817,0.9759696,0.0000204634,0.00003711682,0.0005746316,0.0003989112,0.0004719635,0.02002204,0.00005195737,0.00224599,0.00001335595],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990576,0.0001068448,0.0001996213,0.00001302718,0.000001374251,0.000009506848,0.0003075336,0.000005705493,0.0002987853],"genre_scores_gemma":[0.9975546,0.00009726505,0.000912263,0.00002777658,0.000002122929,0.00000920602,0.0009377656,0.000003035632,0.0004559965],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0344127,"threshold_uncertainty_score":0.06842482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003398426176158561,"score_gpt":0.1882925902834662,"score_spread":0.1848941641073076,"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."}}