{"id":"W4406132388","doi":"10.54796/njb.v12i2.332","title":"Molecular characterization, DNA fingerprinting and genetic diversity analysis of Nepalese rice landraces using SSR markers","year":2024,"lang":"en","type":"article","venue":"Nepal Journal of Biotechnology","topic":"Plant Genetic and Mutation Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Global Institute for Water Security","funders":"Nepal Agricultural Research Council","keywords":"Genetic diversity; Oryza sativa; Microsatellite; Biology; Ex situ conservation; Biotechnology; Genetic variation; DNA profiling; Agriculture; In situ conservation; Allele; Agronomy; Genetics; Population; Ecology; DNA; Medicine; Gene","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":[0.0001630491,0.0001438496,0.0001409054,0.0008467247,0.0002475867,0.0002185682,0.0001423435,0.0001225755,0.000687006],"category_scores_gemma":[0.0003712603,0.00007158764,0.0001969485,0.0005422216,0.0001776223,0.0001178177,0.0001899553,0.0001804898,0.000268479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001181925,"about_ca_system_score_gemma":0.0001717649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001729328,"about_ca_topic_score_gemma":0.003837249,"domain_scores_codex":[0.9998935,0.00001427649,0.00001060294,0.00004098615,0.0000210485,0.00001941919],"domain_scores_gemma":[0.9998218,0.00004846131,0.00004136452,0.00002362406,0.00003764602,0.00002712255],"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":[0.0002481836,0.0001284449,0.1804707,0.0000679951,0.00004973783,0.0008631587,0.001770098,0.0001785739,0.7975085,0.0001935371,0.00005390697,0.01846723],"study_design_scores_gemma":[0.00001790254,0.0004600381,0.9352127,0.00002042011,0.00006277163,0.002158426,0.001253534,0.0009966376,0.05669498,0.000248595,0.002853652,0.00002046911],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988915,0.00004626049,0.0005668646,0.000008867465,7.107986e-7,0.00001016726,0.0001853201,0.000004052611,0.0002862823],"genre_scores_gemma":[0.9955211,0.0001387798,0.00199459,0.00001428351,0.000001897246,0.00003084979,0.00121053,0.000006899267,0.00108115],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001729328,"threshold_uncertainty_score":0.003438473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01242691992366721,"score_gpt":0.2183153997662849,"score_spread":0.2058884798426177,"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."}}