{"id":"W2613520051","doi":"10.1002/ece3.3023","title":"Historical demography and genetic differentiation of the giant freshwater prawn <i>Macrobrachium rosenbergii</i> in Bangladesh based on mitochondrial and dd<scp>RAD</scp> sequence variation","year":2017,"lang":"en","type":"article","venue":"Ecology and Evolution","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Macrobrachium rosenbergii; Biology; Population; Genetic variation; Prawn; Nucleotide diversity; Mitochondrial DNA; Effective population size; Haplotype; Macrobrachium; Zoology; Fishery; Genetics; Genotype; Decapoda; Gene; Crustacean; Demography","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":[0.0002055961,0.0001519848,0.0001570285,0.0007699233,0.0003222079,0.0002395852,0.0002008432,0.0001814335,0.001324878],"category_scores_gemma":[0.0004495659,0.0001174194,0.0001159465,0.0008797768,0.0003682743,0.0002194548,0.0002810329,0.0001863826,0.0002574759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005865912,"about_ca_system_score_gemma":0.0001372101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02219151,"about_ca_topic_score_gemma":0.04801938,"domain_scores_codex":[0.9998412,0.00003248672,0.00001423241,0.00006459542,0.00002325699,0.00002428669],"domain_scores_gemma":[0.9997414,0.00002774209,0.0001121197,0.00001750922,0.00005843558,0.00004280987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009119751,0.00001512,0.9750887,0.00003957812,0.00005745045,0.0004118399,0.0016925,0.0002356594,0.0122317,0.0002194144,0.000223592,0.009693326],"study_design_scores_gemma":[0.000001525615,0.00002732029,0.9983204,0.000007613307,0.000007605659,0.0001600993,0.0007079117,0.00009546118,0.0000994963,0.00002715109,0.0005397669,0.000005615875],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987953,0.0001131791,0.0001062258,0.00002904925,0.000001108294,0.000003542187,0.0002785433,0.000002427453,0.0006705359],"genre_scores_gemma":[0.9994544,0.00009446638,0.00008483787,0.000008730452,8.250008e-7,0.000003500498,0.0001810208,8.547921e-7,0.0001713589],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02219151,"threshold_uncertainty_score":0.04412472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007072648808222969,"score_gpt":0.1999424331128242,"score_spread":0.1928697843046012,"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."}}