{"id":"W3025733080","doi":"10.1101/2020.05.12.086884","title":"SimBit: A high performance, flexible and easy-to-use population genetic simulator","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Computer science; Set (abstract data type); Grid; Simple (philosophy); Code (set theory); Population; Simulation; Programming language; Mathematics","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":[0.001066655,0.0007239625,0.0007045608,0.0004276123,0.0003607142,0.0008811451,0.002093969,0.0009185094,0.01423281],"category_scores_gemma":[0.002605157,0.0005443209,0.0007104449,0.0006763255,0.0003866409,0.0008709092,0.000957787,0.001629769,0.003320822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005318034,"about_ca_system_score_gemma":0.001023513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002658891,"about_ca_topic_score_gemma":0.00193105,"domain_scores_codex":[0.9997106,0.0001167797,0.00001657821,0.00004465186,0.00008019152,0.00003117084],"domain_scores_gemma":[0.9991684,0.0004542609,0.00005041551,0.0001022541,0.0001331642,0.00009158815],"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":[0.0004382762,0.0001555705,0.004949528,0.000449051,0.0002097262,0.0002400972,0.0002375334,0.8658647,0.0134252,0.02472749,0.04864445,0.04065841],"study_design_scores_gemma":[0.0001374792,0.00004204464,0.0003800908,0.0000209892,0.00001824264,0.00004980341,0.00001744427,0.9695225,0.003801374,0.006157783,0.01982896,0.00002325536],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.07893011,0.0004854187,0.8106529,0.0005171882,0.0003469368,0.0002463096,0.01254774,0.07476715,0.02150626],"genre_scores_gemma":[0.4200716,0.0007531503,0.5248709,0.0006226774,0.00008196611,0.001855711,0.01800674,0.01755452,0.01618258],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01423281,"threshold_uncertainty_score":0.0476135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01524013729654104,"score_gpt":0.2078784214094253,"score_spread":0.1926382841128843,"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."}}