{"id":"W2017534056","doi":"10.1007/s11105-014-0804-3","title":"Development of Microsatellite Markers in Tung Tree (Vernicia fordii) Using Cassava Genomic Sequences","year":2014,"lang":"en","type":"article","venue":"Plant Molecular Biology Reporter","topic":"Genetic and Environmental Crop Studies","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Chinese Academy of Tropical Agricultural Sciences; Chinese Academy of Agricultural Sciences; National Natural Science Foundation of China","keywords":"Biology; Microsatellite; Metabolomics; Proteomics; Tree (set theory); Computational biology; Botany; Biotechnology; Genetics; Bioinformatics; Gene; Mathematics","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":[0.0003547455,0.0003541347,0.0003129653,0.0008659381,0.000337408,0.0003832032,0.0004653414,0.0004689135,0.00106466],"category_scores_gemma":[0.0006144409,0.0006289839,0.0004599938,0.0005921258,0.0002447097,0.0001993902,0.0004719754,0.0007888723,0.0006451427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003930874,"about_ca_system_score_gemma":0.0005182479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003139341,"about_ca_topic_score_gemma":0.01065169,"domain_scores_codex":[0.9997219,0.00003196369,0.00003766086,0.0001206662,0.00004652908,0.00004126693],"domain_scores_gemma":[0.9993681,0.0002310805,0.000149072,0.00006531677,0.00008768852,0.00009876608],"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":[0.00005024964,0.0000148135,0.0008594884,0.00002409776,0.000006054529,0.00005496011,0.00007564284,0.00009117553,0.9965498,0.00007562336,0.00001756564,0.00218051],"study_design_scores_gemma":[0.00007315032,0.0003936239,0.05505728,0.00005283119,0.0001680915,0.0005901657,0.0002534372,0.002428262,0.9317782,0.0001702688,0.008999665,0.00003506291],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9482287,0.0004188445,0.0448812,0.000150226,0.00005867332,0.0003329721,0.002404066,0.0004616485,0.003063611],"genre_scores_gemma":[0.9124672,0.0005933565,0.06566797,0.0001960468,0.00001872272,0.0003537047,0.01316234,0.0003086708,0.007231907],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003139341,"threshold_uncertainty_score":0.006242156,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02216091385540415,"score_gpt":0.2214721329405124,"score_spread":0.1993112190851082,"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."}}