{"id":"W1525616393","doi":"","title":"Global trends: foresight of geopolitics, technology, business and humanity in the first quarter of the 21th century and implications for housing and urban management","year":2004,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Global Urban Networks and Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Futures studies; Quarter (Canadian coin); Humanity; Geopolitics; Economy; Political science; Economic growth; Regional science; Economic geography; Geography; Economics; Archaeology; Politics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009000106,0.0001206171,0.0002368617,0.000169227,0.0003254651,0.0000801275,0.0004438712,0.0002277327,9.731601e-7],"category_scores_gemma":[0.0001086002,0.00009397251,0.00004300987,0.0002879011,0.001367881,0.00004551954,0.0005460571,0.0002503238,1.334836e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003956478,"about_ca_system_score_gemma":0.0001743287,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001782519,"about_ca_topic_score_gemma":0.04116167,"domain_scores_codex":[0.9987948,0.00008416361,0.0003115584,0.0003304613,0.0001059844,0.0003730613],"domain_scores_gemma":[0.9991541,0.0001642205,0.0001536853,0.0003923452,0.00008819038,0.00004746315],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00002752192,0.0001242303,0.350279,0.000383602,0.00004920895,9.867632e-7,0.001873451,0.001227925,1.356041e-7,0.613907,0.0001167856,0.03201007],"study_design_scores_gemma":[0.0005450941,0.00003231485,0.7822679,0.0003130941,0.00002659192,0.000001853316,0.006936097,0.0006198531,2.589446e-7,0.2005993,0.008496348,0.0001612637],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9580202,0.001375827,0.00002252228,0.00607353,0.0001456134,0.001554371,0.0002702636,0.00001269403,0.03252495],"genre_scores_gemma":[0.9916101,0.007957732,0.0002286289,0.00004417943,0.0000433091,0.00007078157,0.000007717158,0.000007211664,0.00003032122],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4319888,"threshold_uncertainty_score":0.9763346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01893159568476196,"score_gpt":0.3064683011399849,"score_spread":0.2875367054552229,"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."}}