{"id":"W2433342927","doi":"10.4238/2015.september.8.20","title":"Genetic bottlenecks in Turkish okra germplasm and utility of iPBS retrotransposon markers for genetic diversity assessment","year":2015,"lang":"en","type":"article","venue":"Genetics and Molecular Research","topic":"Chromosomal and Genetic Variations","field":"Agricultural and Biological Sciences","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Alberta Agricultural Research Institute","keywords":"Retrotransposon; Genetic diversity; Germplasm; Biology; Genetic variation; Genetics; Genome; Primer (cosmetics); Population; Evolutionary biology; Biotechnology; Transposable element; Gene; Botany; Medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005658627,0.0001072747,0.0001641205,0.00002616985,0.0002525407,0.00006032567,0.0002232144,0.0001079078,0.00002282954],"category_scores_gemma":[0.00005661295,0.00006086431,0.00004116271,0.0001653811,0.0001957709,0.00001962562,0.0003841503,0.0001252095,3.967389e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001977543,"about_ca_system_score_gemma":0.00003349684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007007108,"about_ca_topic_score_gemma":0.0006397236,"domain_scores_codex":[0.9985737,0.0001529362,0.0002029975,0.0003600376,0.0003853198,0.0003250704],"domain_scores_gemma":[0.9993603,0.0001020325,0.00003535259,0.0001111744,0.0001848075,0.0002063268],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001148869,0.0001730636,0.6505843,0.0000579342,0.00003119405,0.00001035164,0.0002126068,0.00001864901,0.2898394,0.00009113537,0.0005030109,0.05836347],"study_design_scores_gemma":[0.0005491641,0.0005985171,0.987675,0.00001501547,0.00001410746,0.000003340499,0.0001501234,0.002158881,0.004173761,0.002560342,0.001977194,0.0001245877],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968311,0.001488043,0.0001253447,0.0005893116,0.00003204326,0.0005284896,0.0001234147,0.000004729653,0.0002774814],"genre_scores_gemma":[0.996678,0.0005327862,0.002667623,0.00002818359,0.00002393782,0.00002740697,0.00001390046,0.000001768365,0.00002638755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3370906,"threshold_uncertainty_score":0.2481975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07724835287579478,"score_gpt":0.3235785206004432,"score_spread":0.2463301677246484,"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."}}