{"id":"W4211016754","doi":"10.1111/ddi.13488","title":"Winners and losers in a changing climate: how will protected areas conserve red list species under climate change?","year":2022,"lang":"en","type":"article","venue":"Diversity and Distributions","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; National Research Foundation","keywords":"IUCN Red List; Threatened species; Climate change; Protected area; Range (aeronautics); Biodiversity; Geography; IUCN protected area categories; Ecology; Species distribution; Near-threatened species; Nature reserve; Global biodiversity; Environmental resource management; Environmental science; Habitat; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003500317,0.0002693101,0.0003655644,0.0006941152,0.0006116649,0.002059321,0.0007653689,0.0004669057,0.004435382],"category_scores_gemma":[0.00829798,0.0001234259,0.0002947918,0.000609075,0.001177706,0.002571949,0.001134658,0.0006797872,0.0003433764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001001476,"about_ca_system_score_gemma":0.0005680402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01051828,"about_ca_topic_score_gemma":0.02001233,"domain_scores_codex":[0.9991716,0.0004020291,0.00002509193,0.0001323153,0.0001115226,0.0001574647],"domain_scores_gemma":[0.9972442,0.0007800683,0.0009921968,0.0002074516,0.0003395344,0.0004366033],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005096598,0.0001160191,0.8044873,0.0003007226,0.0003846782,0.0002298354,0.001536215,0.05095887,0.002801999,0.01053235,0.005386935,0.1227553],"study_design_scores_gemma":[0.00003693883,0.0006134443,0.8316957,0.0003538225,0.0001769085,0.0002311208,0.007843614,0.1209282,0.001450348,0.02572054,0.01084378,0.0001056331],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9815972,0.0008220465,0.003502389,0.00450662,0.00007772688,0.00002256011,0.0004541153,0.00004387814,0.008973495],"genre_scores_gemma":[0.9988678,0.0001305997,0.0005197758,0.0000995221,0.00001456112,0.000006279118,0.000077246,0.00000584688,0.0002785556],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01051828,"threshold_uncertainty_score":0.02091414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03825081736469536,"score_gpt":0.2155572720827355,"score_spread":0.1773064547180402,"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."}}