{"id":"W2294554663","doi":"10.3386/w22175","title":"Distance and Time Effects in Swedish Commodity Prices, 1732–1914","year":2016,"lang":"en","type":"preprint","venue":"National Bureau of Economic Research","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Social Sciences and Humanities Research Council of Canada; National Science Foundation","keywords":"Commodity; Economics; Econometrics; Monetary economics; Financial economics; Market economy","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":[0.0006092521,0.0003972394,0.0003640963,0.00300636,0.0006096421,0.001134811,0.0003556072,0.0003122015,0.002386414],"category_scores_gemma":[0.003479553,0.0002051537,0.0006199554,0.005454259,0.001129418,0.00061663,0.001253481,0.0005878211,0.0004941801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001251037,"about_ca_system_score_gemma":0.0005983462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1155446,"about_ca_topic_score_gemma":0.08878956,"domain_scores_codex":[0.9994994,0.000110302,0.00004017277,0.0001196481,0.0001087225,0.0001217678],"domain_scores_gemma":[0.9981213,0.0007358606,0.0006090995,0.0001130298,0.0002963637,0.0001242665],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000396831,0.0000551214,0.9547607,0.00007136424,0.0005056731,0.001244863,0.003900237,0.009911054,0.0008344793,0.003926924,0.001840477,0.02255216],"study_design_scores_gemma":[0.00001216769,0.00004911798,0.9893308,0.00004308394,0.0001066599,0.0001647387,0.002306022,0.001643622,0.000261909,0.001179448,0.004874879,0.00002765262],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971782,0.0005841442,0.0001681547,0.00009988455,0.00001475574,8.922037e-7,0.0004896999,0.000005625463,0.001458691],"genre_scores_gemma":[0.9980596,0.0002873448,0.0001093339,0.000006133658,0.00001523178,0.000001892938,0.0008227844,0.000009077399,0.0006886931],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1155446,"threshold_uncertainty_score":0.229744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2627463039038728,"score_gpt":0.4126279236557792,"score_spread":0.1498816197519063,"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."}}