{"id":"W3089274602","doi":"10.1108/s0363-326820200000036004","title":"Improving Deflators for Estimating Canadian Economic Growth, 1870–1900","year":2020,"lang":"en","type":"book-chapter","venue":"Research in economic history","topic":"Historical Economic and Social Studies","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Clothing; Price index; Economics; Consumer price index (South Africa); Index (typography); Fell; Product (mathematics); Gross domestic product; Relative price; National accounts; Agricultural economics; Econometrics; Geography; Macroeconomics; Mathematics; Cartography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002172475,0.0009559004,0.0004053034,0.01109013,0.001226046,0.001879095,0.001010488,0.0002385954,0.007912043],"category_scores_gemma":[0.01104355,0.0002904725,0.0005708897,0.01415557,0.0004812589,0.0006538604,0.0007371468,0.0009955757,0.00254105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02975634,"about_ca_system_score_gemma":0.02178296,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9897138,"about_ca_topic_score_gemma":0.9858942,"domain_scores_codex":[0.9982675,0.0001102495,0.00008006194,0.0001932409,0.001141922,0.0002069328],"domain_scores_gemma":[0.9923702,0.000456327,0.0003651356,0.000252582,0.006337065,0.0002186015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001233423,0.00007089406,0.4149061,0.0004391283,0.0002206602,0.0002034302,0.001164538,0.02233187,0.0008812411,0.03025725,0.2523269,0.2770746],"study_design_scores_gemma":[0.0000265428,0.00002134242,0.7330645,0.0002290666,0.00005521252,0.00009133293,0.0009288178,0.02729115,0.001335009,0.001639621,0.2352439,0.00007342104],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.3184341,0.008340749,0.04413122,0.002579704,0.0009608463,0.0004547845,0.4539477,0.003740344,0.1674107],"genre_scores_gemma":[0.5792935,0.005955854,0.06057682,0.0003244183,0.0002231994,0.0004383443,0.3144896,0.000740463,0.03795775],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02975634,"threshold_uncertainty_score":0.2158983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1211042937615534,"score_gpt":0.2739003421036197,"score_spread":0.1527960483420663,"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."}}