{"id":"W3135363434","doi":"10.1111/1755-0998.13372","title":"SimBit: A high performance, flexible and easy‐to‐use population genetic simulator","year":2021,"lang":"en","type":"article","venue":"Molecular Ecology Resources","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Biology; Population; Selection (genetic algorithm); Selfing; Epistasis; Effective population size; Coalescent theory; Evolutionary biology; Statistics; Computer science; Genetic variation; Genetics; Machine learning; Mathematics; Demography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001120533,0.001037786,0.0008150319,0.0004715938,0.0003335086,0.0009769235,0.002696042,0.0009916419,0.02084883],"category_scores_gemma":[0.004216657,0.000728454,0.0009296483,0.000680026,0.0003559323,0.00106073,0.0009989258,0.001837965,0.005079866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006630746,"about_ca_system_score_gemma":0.0012303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005283729,"about_ca_topic_score_gemma":0.004650426,"domain_scores_codex":[0.9996805,0.0001210969,0.00002459485,0.00005682995,0.00008136758,0.00003565307],"domain_scores_gemma":[0.9985107,0.0009530294,0.00007608665,0.0001407363,0.0002063529,0.0001131538],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004372958,0.0001446226,0.00503728,0.000595831,0.0002632372,0.0002433827,0.0002418725,0.8589894,0.005692699,0.01457124,0.06785826,0.04592491],"study_design_scores_gemma":[0.0001859299,0.00003931822,0.0003602332,0.00002468312,0.00003107976,0.0000555034,0.00001824894,0.9684352,0.002408104,0.006120018,0.02229534,0.00002637164],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.04372809,0.0004749029,0.7817233,0.0004795131,0.0003147882,0.0003122339,0.02186914,0.1326201,0.01847799],"genre_scores_gemma":[0.3833702,0.001039696,0.5353411,0.001002244,0.00008754656,0.002654892,0.03196114,0.02712405,0.01741912],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.02084883,"threshold_uncertainty_score":0.06974632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007284709927424676,"score_gpt":0.206891361719606,"score_spread":0.1996066517921813,"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."}}