{"id":"W4405944732","doi":"10.1111/ele.14512","title":"The Demographic Basis of Population Growth: A 32‐Year Transient Life Table Response Experiment","year":2024,"lang":"en","type":"article","venue":"Ecology Letters","topic":"Demographic Trends and Gender Preferences","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institut écologie et environnement; Natural Sciences and Engineering Research Council of Canada; Directorate for Biological Sciences; Centre National de la Recherche Scientifique; Université de Strasbourg; Alberta Parks; Fondation Fyssen; National Science Foundation","keywords":"Ecology; Table (database); Population; Population growth; Biology; Environmental science; Geography; Demography; Statistics; Mathematics; Computer science","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":[0.001322283,0.00009082269,0.0001297175,0.0001959854,0.0004855215,0.00007170914,0.0002236407,0.00008795606,0.0001551952],"category_scores_gemma":[0.0001338823,0.00006769279,0.0001214649,0.000639269,0.0003855417,0.0001059022,0.00001955022,0.0001208484,0.00001127433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000372507,"about_ca_system_score_gemma":0.00008753608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001229477,"about_ca_topic_score_gemma":0.004647767,"domain_scores_codex":[0.9983737,0.0006098326,0.0002271565,0.0002301421,0.0002459657,0.0003132385],"domain_scores_gemma":[0.9990603,0.0006460093,0.00005005063,0.0001324112,0.00002873844,0.0000825074],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001218874,0.0003595043,0.5735979,0.0001006398,0.001291249,0.00006816604,0.09879485,0.0001155265,0.009604939,0.1487013,0.1496109,0.01653617],"study_design_scores_gemma":[0.0003076794,0.0001634434,0.9355719,0.00002777974,0.00008046167,0.000001298493,0.006677235,0.00005962049,0.000205133,0.00203431,0.05465512,0.0002159873],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9356006,0.0007125259,0.00005532533,0.06142373,0.00098722,0.0001577682,0.000006698387,0.00007691327,0.000979255],"genre_scores_gemma":[0.9985971,0.0002264034,0.0001011237,0.0007653896,0.0000850557,0.00004016763,0.00000359337,0.000007851704,0.0001733525],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.361974,"threshold_uncertainty_score":0.3734288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01871211232067297,"score_gpt":0.279280062096597,"score_spread":0.260567949775924,"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."}}