{"id":"W4380027698","doi":"10.5194/egusphere-2023-992","title":"Documents, Reanalysis, and Global Circulation Models: A New Method for Reconstructing Historical Climate Focusing on Present-day Inland Tanzania, 1856–1890","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Global Maritime and Colonial Histories","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Climate Program Office; Social Sciences and Humanities Research Council of Canada; Biological and Environmental Research; Office of Science; National Oceanic and Atmospheric Administration; U.S. Department of Energy","keywords":"Proxy (statistics); Documentary evidence; Tanzania; Climatology; Climate change; Weighting; Geography; Period (music); History; Computer science; Archaeology; Geology; Environmental planning","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":[0.001623878,0.0005471269,0.0002531274,0.004889413,0.0004539159,0.001702729,0.0004674189,0.0003170022,0.001558667],"category_scores_gemma":[0.007359772,0.0003264433,0.0004681114,0.004265307,0.0003777333,0.001111854,0.0009720515,0.0006431846,0.0004073379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006057246,"about_ca_system_score_gemma":0.001556235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01344146,"about_ca_topic_score_gemma":0.03140599,"domain_scores_codex":[0.9995522,0.0001588504,0.00005182196,0.0001257928,0.00008960882,0.00002171489],"domain_scores_gemma":[0.99832,0.0006130776,0.0003328139,0.0003998828,0.0002678556,0.00006623413],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000201444,0.0001064692,0.1104747,0.0004218594,0.0006001043,0.0003016633,0.005021385,0.03259543,0.007290019,0.03297536,0.01451199,0.7954994],"study_design_scores_gemma":[0.0001895961,0.0001989694,0.2259495,0.0006597643,0.0004768993,0.0005530967,0.005539009,0.4259058,0.01492231,0.08173683,0.2435853,0.0002828864],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1945472,0.001990553,0.7664487,0.001194371,0.0002421208,0.0002889266,0.01982585,0.005170874,0.01029148],"genre_scores_gemma":[0.3030945,0.0005538968,0.6882293,0.00005199517,0.0000832054,0.0002557502,0.005984576,0.0003359845,0.001410824],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01344146,"threshold_uncertainty_score":0.02672642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0682988389774335,"score_gpt":0.3642335169049403,"score_spread":0.2959346779275068,"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."}}