{"id":"W2091613085","doi":"10.3732/apps.1300013","title":"Microsatellite markers for Russian olive (<i>Elaeagnus angustifolia</i>; Elaeagnaceae)","year":2013,"lang":"en","type":"article","venue":"Applications in Plant Sciences","topic":"Phytochemical and Pharmacological Studies","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Biology; Microsatellite; Locus (genetics); Allele; Population; Genetic marker; Botany; Genetics; Gene","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001842534,0.0001113297,0.0001859091,0.00006384817,0.0002267883,0.00002786847,0.0001924733,0.00005423662,0.0001243159],"category_scores_gemma":[0.00004149212,0.00007345725,0.00005512639,0.0004298226,0.000396026,0.00009425056,0.00004550926,0.0001004782,0.00008183349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003241367,"about_ca_system_score_gemma":0.00003371326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000111766,"about_ca_topic_score_gemma":0.000009182169,"domain_scores_codex":[0.9990149,0.00001144162,0.0002164469,0.0003161164,0.0001327885,0.0003083547],"domain_scores_gemma":[0.99933,0.0003680412,0.00005572106,0.0001038666,0.00003353335,0.0001087918],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004348406,0.002366954,0.3525642,0.0006992412,0.0002327268,0.00001444411,0.001271586,0.00005426277,0.4229925,0.06541209,0.08504123,0.06891588],"study_design_scores_gemma":[0.00314285,0.0009036901,0.4821598,0.0002984177,0.0002089529,0.00007989929,0.001782197,0.002866676,0.09096487,0.08050089,0.3360461,0.001045717],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9566079,0.002023618,0.0009358383,0.005250975,0.0001015443,0.003611875,0.0001657239,0.00009942315,0.03120305],"genre_scores_gemma":[0.9898893,0.000388663,0.006162304,0.001138814,0.00009206005,0.001885233,0.00004834619,0.000004707788,0.000390622],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3320276,"threshold_uncertainty_score":0.2995499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03784931263755863,"score_gpt":0.3101341727107866,"score_spread":0.272284860073228,"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."}}