{"id":"W2567659964","doi":"10.1111/geb.12555","title":"Impacts of global change on species distributions: obstacles and solutions to integrate climate and land use","year":2016,"lang":"en","type":"article","venue":"Global Ecology and Biogeography","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":197,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Queen's University; Queen's University Belfast","keywords":"Climate change; Biodiversity; Global change; Ecology; Abundance (ecology); Habitat; Environmental resource management; Land use, land-use change and forestry; Global warming; Species distribution; Geography; Land use; Environmental science; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001161281,0.0001454844,0.0001686919,0.00002697318,0.0002114642,0.00003414412,0.00006935983,0.0001030074,0.0006574373],"category_scores_gemma":[0.00006556813,0.0000972422,0.00004427872,0.0003452201,0.0007705651,0.0001646227,0.0002456992,0.00003199737,0.00004281995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001288115,"about_ca_system_score_gemma":0.000003565287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007870361,"about_ca_topic_score_gemma":0.009937342,"domain_scores_codex":[0.9990628,0.00004055477,0.0001489876,0.0002824847,0.00008763868,0.000377584],"domain_scores_gemma":[0.9995542,0.00005417334,0.00005953131,0.0001142413,0.00001668736,0.0002011569],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000705214,0.00006464507,0.9811162,0.000005347255,0.00001536148,0.000002683782,0.00001528523,1.806101e-8,0.0003115112,0.01543598,0.001025807,0.001936689],"study_design_scores_gemma":[0.0004061314,0.0003014809,0.9914861,0.00002186038,0.00002234076,0.00001775057,0.0001603883,6.750058e-7,0.00005621177,0.0008168528,0.006587231,0.0001229746],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9871221,0.0002644176,0.000013232,0.002303658,0.00009219764,0.0001933152,0.00926279,0.00002705045,0.0007212985],"genre_scores_gemma":[0.9969378,0.002521863,0.00003677599,0.0004232224,0.00001242814,0.00001771207,0.00004430141,0.00000204814,0.000003836298],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01461912,"threshold_uncertainty_score":0.7198477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0287385330288236,"score_gpt":0.2485733114030724,"score_spread":0.2198347783742488,"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."}}