{"id":"W2911529453","doi":"10.1111/ecog.04264","title":"A macroecological approach to evolutionary rescue and adaptation to climate change","year":2019,"lang":"en","type":"article","venue":"Ecography","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Genetics","funders":"","keywords":"Biological dispersal; Climate change; Ecology; Range (aeronautics); Niche; Species distribution; Adaptation (eye); Population; Environmental niche modelling; Environmental change; Abiotic component; Evolutionary ecology; Biology; Ecological niche; Habitat","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001336055,0.00009522923,0.00009539449,0.000066159,0.00009866949,0.0000249367,0.0001027559,0.00005086616,0.009909445],"category_scores_gemma":[0.00001026851,0.0000861177,0.00004503295,0.0004594995,0.00004726421,0.0001116207,0.0001986553,0.00005219016,0.00383166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008997561,"about_ca_system_score_gemma":0.000001054684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006926057,"about_ca_topic_score_gemma":0.000102823,"domain_scores_codex":[0.9991019,0.00002508275,0.0001117123,0.0003191325,0.0001630826,0.0002790807],"domain_scores_gemma":[0.9996485,0.0000121434,0.00001983422,0.0001412953,0.000006705919,0.0001715228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001807507,0.0004682411,0.9440175,0.00003845724,0.0000161057,0.000004144022,0.002900287,0.0001706323,0.002114052,0.0080138,0.02686886,0.01520713],"study_design_scores_gemma":[0.0001606987,0.000143222,0.9611194,0.000003891462,0.000003718218,0.00000415095,0.00126631,0.0004057813,0.00001233569,0.00006876495,0.03667653,0.000135155],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9348883,0.00003999301,0.00007761765,0.0007168138,0.0001065518,0.0005860651,0.00007721713,0.00005656339,0.0634509],"genre_scores_gemma":[0.9959164,0.00004996823,0.001855491,0.001829082,0.00002671179,0.0001753549,0.00004906529,0.00000708334,0.00009082419],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06336008,"threshold_uncertainty_score":0.996944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03650743200882617,"score_gpt":0.2370039794234509,"score_spread":0.2004965474146247,"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."}}