{"id":"W4417367810","doi":"10.1111/ele.70283","title":"Linking Climate and Demography to Predict Population Dynamics and Persistence Under Global Change","year":2025,"lang":"en","type":"article","venue":"Ecology Letters","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Rice University; Hatch; Division of Environmental Biology; U.S. Department of Agriculture; National Institute of Food and Agriculture; National Science Foundation","keywords":"Climate change; Vital rates; Population; Biodiversity; Ecological forecasting; Inference; Global warming; Population growth","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":[0.003227839,0.00038169,0.0002802257,0.001483942,0.0003595051,0.001968045,0.0005850735,0.001348391,0.001792783],"category_scores_gemma":[0.02329931,0.0003343901,0.0005293207,0.001262782,0.001012592,0.004406836,0.001256799,0.001411261,0.0003682316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000995781,"about_ca_system_score_gemma":0.0005400314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01108758,"about_ca_topic_score_gemma":0.0108092,"domain_scores_codex":[0.9995133,0.000274378,0.00003428429,0.00009833557,0.00004160614,0.00003807464],"domain_scores_gemma":[0.9942518,0.00416678,0.0006141174,0.0004997664,0.0003302785,0.0001371957],"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":[0.00004903164,0.00003400296,0.275622,0.0001497408,0.0002949629,0.00009317508,0.0004364041,0.6295128,0.0005601707,0.0414363,0.002377069,0.04943438],"study_design_scores_gemma":[0.000009523518,0.00002897942,0.07598349,0.0001500425,0.00005966294,0.00007743855,0.0006137656,0.7159916,0.0003915499,0.2006322,0.005980344,0.00008140791],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.67274,0.00335177,0.2824368,0.02070002,0.0002455238,0.00004413022,0.003189077,0.0006295255,0.01666317],"genre_scores_gemma":[0.9827145,0.001722462,0.01400237,0.0002887121,0.00008984226,0.0000242655,0.0006331772,0.00007546871,0.0004492773],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01108758,"threshold_uncertainty_score":0.02204609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0156780513016397,"score_gpt":0.2374182170347079,"score_spread":0.2217401657330682,"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."}}