{"id":"W2610199988","doi":"10.1101/104240","title":"Multilevel and sex-specific selection on competitive traits in North American red squirrels","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Animal Ecology and Behavior Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of Saskatchewan; University of Alberta; University of Guelph","funders":"Ontario Ministry of Research and Innovation; National Science Foundation","keywords":"Selection (genetic algorithm); Biology; Natural selection; Population; Demography; Multilevel model; Group selection; Ecology; Statistics","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":[0.0004105488,0.0001381314,0.0001968548,0.000408028,0.0002237316,0.0002356857,0.0001389169,0.0001114974,0.001275288],"category_scores_gemma":[0.0004841021,0.00008371313,0.0001385797,0.0001773113,0.0002387374,0.0001028851,0.0002155563,0.0001433136,0.0001091129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001871027,"about_ca_system_score_gemma":0.0001088644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004687988,"about_ca_topic_score_gemma":0.02709292,"domain_scores_codex":[0.9998288,0.00003955581,0.000008911315,0.00006534089,0.00003804031,0.00001935423],"domain_scores_gemma":[0.9996291,0.00008392614,0.0001206227,0.00003970311,0.00006136034,0.00006526987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001309673,0.0000667611,0.9500312,0.00002335899,0.0001133303,0.0001016809,0.000500768,0.0002622544,0.04234571,0.00006675346,0.0001336423,0.006223552],"study_design_scores_gemma":[0.000001802054,0.00004831674,0.9992909,0.000001770963,0.000007921806,0.00004300864,0.0000971168,0.0002192398,0.0002068348,0.00001633128,0.00006449125,0.000002213539],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997956,0.00001599637,0.00004428492,0.000003265382,5.903092e-7,7.591875e-7,0.00004451267,0.000001763649,0.00009319047],"genre_scores_gemma":[0.99972,0.000009984197,0.00009988345,0.000008721087,0.000001116282,0.000003094772,0.00006955482,0.000001447516,0.00008616554],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004687988,"threshold_uncertainty_score":0.009321392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02117266031820832,"score_gpt":0.2363769404041693,"score_spread":0.215204280085961,"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."}}