{"id":"W4405292570","doi":"10.1007/978-3-031-67563-8_22","title":"Klimaveränderungen durch die Zeitalter","year":2024,"lang":"de","type":"book-chapter","venue":"","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Political science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006471438,0.000735515,0.0004481704,0.000961998,0.0006404329,0.003452534,0.0005864878,0.0007291686,0.02120879],"category_scores_gemma":[0.002851874,0.0006321571,0.000471169,0.001880709,0.001821974,0.004511257,0.001264253,0.002087923,0.005412668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001439873,"about_ca_system_score_gemma":0.0006480273,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002371386,"about_ca_topic_score_gemma":0.002558217,"domain_scores_codex":[0.9996595,0.00006892326,0.00002785585,0.0000904465,0.0001209124,0.00003225824],"domain_scores_gemma":[0.999379,0.0003359624,0.00008408145,0.00008665862,0.00008308674,0.00003112308],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001502084,0.000009095002,0.0002580257,0.00008528965,0.000009624155,0.00004060636,0.0002969087,0.003711888,0.001101765,0.9211587,0.01172446,0.06158859],"study_design_scores_gemma":[0.000003500896,0.00001085537,0.0008547331,0.00007196789,0.00001232669,0.0001869743,0.0002104392,0.00587705,0.001549252,0.805953,0.1852456,0.00002428155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02089152,0.04190396,0.3495978,0.0058177,0.002652444,0.00004074413,0.001121163,0.0008629983,0.5771117],"genre_scores_gemma":[0.4170544,0.03923488,0.1054182,0.001096205,0.002154549,0.0002292099,0.001081555,0.001317861,0.4324131],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02120879,"threshold_uncertainty_score":0.07095051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1337642070171081,"score_gpt":0.357650279198015,"score_spread":0.2238860721809069,"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."}}