{"id":"W2996205625","doi":"10.1002/ajb2.1400","title":"Integrated empirical approaches to better understand species’ range limits","year":2019,"lang":"en","type":"article","venue":"American Journal of Botany","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biology; Range (aeronautics); Evolutionary biology; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.03817922,0.001518594,0.002472758,0.009837062,0.001521578,0.006411586,0.003701532,0.002054695,0.009008217],"category_scores_gemma":[0.1027458,0.0006673835,0.00157247,0.009720619,0.006317333,0.01193823,0.007871622,0.00603826,0.0006459936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003084301,"about_ca_system_score_gemma":0.002329179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005066861,"about_ca_topic_score_gemma":0.005233747,"domain_scores_codex":[0.9743299,0.01810262,0.0009527869,0.003680171,0.002509828,0.0004247225],"domain_scores_gemma":[0.877228,0.1040745,0.007245083,0.006546866,0.003927957,0.0009775405],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001354375,0.0006529838,0.1708745,0.003350096,0.005729912,0.0006254301,0.0126457,0.02112286,0.0006608057,0.5792876,0.009058747,0.1958559],"study_design_scores_gemma":[0.00005757893,0.0003081789,0.06791589,0.001861091,0.0005818661,0.0003155759,0.01141814,0.04995589,0.0002575655,0.8199366,0.04728333,0.0001081645],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1843208,0.05270079,0.6607389,0.02501899,0.0006749905,0.001179848,0.004678321,0.0004451337,0.07024234],"genre_scores_gemma":[0.7927322,0.01320034,0.1829823,0.004278153,0.0006610458,0.001766037,0.002100723,0.0001448967,0.002134314],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03817922,"threshold_uncertainty_score":0.2019134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1082088732801221,"score_gpt":0.2621385979073469,"score_spread":0.1539297246272248,"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."}}