{"id":"W4281259496","doi":"10.1111/ele.14028","title":"The role of demographic compensation in stabilising marginal tree populations in North America","year":2022,"lang":"en","type":"letter","venue":"Ecology Letters","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of Alberta; University of Alberta; Agriculture Food and Rural Development; University of British Columbia","funders":"China Scholarship Council; National Natural Science Foundation of China","keywords":"Ecology; Range (aeronautics); Climate change; Population; Population size; Biology; Compensation (psychology); Population growth; Competition (biology); Geography; Demography","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":[],"category_scores_codex":[0.0001525536,0.0001351618,0.0001999359,0.0001331499,0.0001604679,0.00001312324,0.0003002138,0.000112116,0.01505031],"category_scores_gemma":[0.00002739577,0.0001261748,0.00007390806,0.0006135948,0.0003858393,0.00005719837,0.0001456055,0.0007311678,0.00005837084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009840952,"about_ca_system_score_gemma":0.000008574574,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001047012,"about_ca_topic_score_gemma":0.08595622,"domain_scores_codex":[0.9985827,0.0002635702,0.0003235221,0.0002603015,0.0002285077,0.0003414091],"domain_scores_gemma":[0.9993708,0.0001826757,0.0002043349,0.0002221809,0.000003411601,0.0000166651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001082796,0.0000307276,0.902788,0.000003210563,0.000005290925,0.00002584788,0.0001659829,0.0004234696,0.0001224484,0.00001467666,0.09591965,0.000489888],"study_design_scores_gemma":[0.0001268338,0.00002340103,0.7283446,0.000001424172,0.000006854774,0.000002066803,0.0004513153,0.00008610063,0.00000137899,0.00003666339,0.270831,0.00008844733],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7475556,0.00002293439,0.00000189994,0.2506404,0.0001817667,0.0002179885,0.00006427718,0.000009610874,0.001305459],"genre_scores_gemma":[0.7907921,0.00005020878,0.00003938243,0.2072688,0.00007490827,0.0001376738,0.001571544,0.00002247397,0.00004288576],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1749113,"threshold_uncertainty_score":0.9858501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02040402484723763,"score_gpt":0.2282712457238819,"score_spread":0.2078672208766443,"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."}}