{"id":"W6944987950","doi":"10.20381/ruor-30537","title":"An Investigation of the Use of Linear Mixed Models Under an Extreme Phenotype Sampling (EPS) Design","year":2024,"lang":"en","type":"article","venue":"University of Ottawa - Library","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mixed model; Generalized linear mixed model; Covariate; Population stratification; Population; Linear model; Context (archaeology); Missing data; Type I and type II errors; Extreme value theory","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1388108,0.001573078,0.001706553,0.001184836,0.0009356969,0.002977986,0.003196736,0.002297277,0.002606865],"category_scores_gemma":[0.2431732,0.0008715891,0.00306531,0.001568913,0.002393192,0.003040412,0.003460056,0.004030426,0.0004103324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001634213,"about_ca_system_score_gemma":0.002363406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001901277,"about_ca_topic_score_gemma":0.002170732,"domain_scores_codex":[0.8073172,0.1817145,0.002005208,0.004875773,0.003517867,0.0005694187],"domain_scores_gemma":[0.554239,0.4104162,0.01156755,0.01595551,0.007098944,0.0007228048],"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":[0.001445291,0.0002797325,0.03224166,0.001432352,0.002391842,0.0006640552,0.00255698,0.1624208,0.002299414,0.5414894,0.003405133,0.2493735],"study_design_scores_gemma":[0.0003997256,0.002290984,0.005587188,0.000482652,0.0005724596,0.0004080226,0.0004951637,0.7578133,0.00228661,0.2190092,0.01049318,0.0001615227],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01793653,0.0005118995,0.9782119,0.001013544,0.0001124503,0.0005120665,0.0001818057,0.0001555185,0.001364383],"genre_scores_gemma":[0.1711521,0.0006034033,0.8234669,0.0007755902,0.0001591949,0.002296854,0.0002716582,0.00006837803,0.001205952],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1388108,"threshold_uncertainty_score":0.7341103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1730925690165943,"score_gpt":0.2287521775733838,"score_spread":0.05565960855678959,"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."}}