{"id":"W4220751890","doi":"10.1111/oik.09063","title":"Evaluating ecological uniqueness over broad spatial extents using species distribution modelling","year":2022,"lang":"en","type":"article","venue":"Oikos","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Species richness; Ecology; Species distribution; Beta diversity; Breeding bird survey; Spatial analysis; Spatial distribution; Spatial ecology; Species diversity; Distribution (mathematics); Macroecology; Geography; Habitat; Biology; Mathematics; Remote sensing","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":[0.003649812,0.0007945691,0.0008020744,0.002765604,0.0004763805,0.001123322,0.0007062744,0.0006397521,0.0007685108],"category_scores_gemma":[0.005974593,0.0003873005,0.001255819,0.001697947,0.0005947652,0.001553971,0.001192473,0.0004724163,0.0001625272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000512423,"about_ca_system_score_gemma":0.0003507131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005036042,"about_ca_topic_score_gemma":0.006623216,"domain_scores_codex":[0.999127,0.0004031857,0.00005566475,0.0002674223,0.00009279737,0.00005399423],"domain_scores_gemma":[0.9958344,0.002776612,0.0006990033,0.0003046189,0.0001983857,0.0001870668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001639291,0.00006993415,0.3071653,0.000100349,0.0005348187,0.0001508212,0.0003504663,0.6630377,0.005529831,0.00241553,0.0001604928,0.02032087],"study_design_scores_gemma":[0.000008404388,0.00005081562,0.06637073,0.00001416504,0.00004151206,0.0001038199,0.00009860744,0.9293709,0.0005864208,0.00313845,0.0001874824,0.00002855632],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8717343,0.0001632012,0.1266915,0.0000452613,0.000005085612,0.00003187483,0.0003570134,0.0002186961,0.0007531416],"genre_scores_gemma":[0.9748257,0.00004523004,0.02467261,0.000009394274,0.000004365712,0.00003528248,0.0002631579,0.00002236284,0.0001218805],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005036042,"threshold_uncertainty_score":0.01930231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1253758820431835,"score_gpt":0.3270712990475813,"score_spread":0.2016954170043978,"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."}}