{"id":"W2598363387","doi":"10.1101/117606","title":"Demographic compensation does not rescue populations at a trailing range edge","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Division of Environmental Biology; National Science Foundation","keywords":"Biological dispersal; Population; Vital rates; Range (aeronautics); Ecology; Population growth; Geography; Biology; Climate change; Habitat; Reproduction; Latitude; 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":[0.0003539493,0.0001967825,0.0002392416,0.0002581637,0.00033905,0.0002964044,0.0002764237,0.0001713352,0.001072782],"category_scores_gemma":[0.0009978048,0.00009689617,0.0001713644,0.0001462034,0.0003414716,0.0002337954,0.000344332,0.0002258617,0.0001494489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002930447,"about_ca_system_score_gemma":0.0002333558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002527981,"about_ca_topic_score_gemma":0.007819621,"domain_scores_codex":[0.9999187,0.0000160162,0.000006953676,0.0000225009,0.00001370359,0.00002213968],"domain_scores_gemma":[0.9993358,0.0001162695,0.0002055045,0.000104849,0.000113625,0.0001239235],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002822129,0.0000980919,0.9159824,0.00003872138,0.00007004631,0.0003253105,0.0002607992,0.007603406,0.05198993,0.0006379,0.0004493314,0.02226195],"study_design_scores_gemma":[0.00002945749,0.0004767211,0.9440884,0.00001941436,0.00005181531,0.000624523,0.0005743645,0.04464969,0.006715078,0.001602183,0.001149984,0.00001839341],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990809,0.00001102447,0.0004602576,0.0000203851,0.000001891553,0.00000153255,0.00002753949,0.00001418152,0.0003821926],"genre_scores_gemma":[0.9995359,0.000005358521,0.0002604831,0.0000165548,0.000001403783,0.000001143521,0.00003893063,0.000001682211,0.0001384051],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002527981,"threshold_uncertainty_score":0.00502646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02539425054734152,"score_gpt":0.2423723419507844,"score_spread":0.2169780914034429,"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."}}