{"id":"W4307693399","doi":"10.22541/au.166722317.78861119/v1","title":"Pushed to the edge: Spatial sorting can slow down invasions","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; University of Ottawa","funders":"","keywords":"Allee effect; Sorting; Biological dispersal; Population; Selection (genetic algorithm); Spatial ecology; Enhanced Data Rates for GSM Evolution; Computer science; Spatial dependence; Ecology; Biological system; Biology; Mathematics; Artificial intelligence; Statistics; Algorithm; 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":[0.0005803187,0.0004258099,0.0005292062,0.00052335,0.0006681386,0.001910702,0.0007069386,0.001757959,0.004579823],"category_scores_gemma":[0.003417643,0.0002857012,0.0005140718,0.0003010133,0.001426451,0.002596516,0.00138296,0.001042278,0.0006650314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000510168,"about_ca_system_score_gemma":0.0003534088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007704775,"about_ca_topic_score_gemma":0.0006254152,"domain_scores_codex":[0.9997259,0.00005141722,0.00001222495,0.00007718167,0.00006057002,0.00007270891],"domain_scores_gemma":[0.9985877,0.0006128033,0.0002695587,0.000206097,0.0001139263,0.0002099832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008848028,0.0003131615,0.01561638,0.0007281036,0.0001884501,0.001506183,0.001110126,0.07982616,0.3298237,0.4738925,0.004767555,0.09134281],"study_design_scores_gemma":[0.0003371404,0.0007974023,0.01376494,0.0001223752,0.0002660932,0.001366757,0.0007605322,0.4011981,0.06996567,0.4814582,0.02973285,0.0002299459],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8859256,0.001816177,0.08459047,0.003376327,0.0002673572,0.0000247337,0.0001038872,0.0007711436,0.02312429],"genre_scores_gemma":[0.9907245,0.0004884324,0.005643242,0.0003928476,0.00003394836,0.0000129252,0.00002683877,0.00005079794,0.002626611],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004579823,"threshold_uncertainty_score":0.01532102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01654410980338415,"score_gpt":0.2613039361990351,"score_spread":0.244759826395651,"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."}}