{"id":"W6966338668","doi":"10.3886/e129221v1-171723","title":"Market integration from the Black Death to the First World War","year":2025,"lang":"en","type":"dataset","venue":"ICPSR Data Holdings","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Convergence (economics); First world war; Rest (music); Divergence (linguistics); Market integration; Quarter (Canadian coin); Football","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":[0.001377854,0.0007145478,0.0008297153,0.003766761,0.0007409673,0.003048855,0.001376063,0.001118817,0.0291374],"category_scores_gemma":[0.006089308,0.0003620038,0.0007847553,0.00845482,0.0004922612,0.002234745,0.002484147,0.001933378,0.02228716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001834553,"about_ca_system_score_gemma":0.001975854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09329513,"about_ca_topic_score_gemma":0.08814429,"domain_scores_codex":[0.9987296,0.0002248104,0.0001437877,0.0002739656,0.0003431481,0.0002846288],"domain_scores_gemma":[0.9976985,0.0003611477,0.0005714666,0.0003628577,0.0007698429,0.0002361094],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00009910805,0.0000152808,0.003388936,0.0004361732,0.00003919779,0.00004909701,0.0001182328,0.0002493735,0.0000437157,0.002464434,0.9864405,0.006655977],"study_design_scores_gemma":[0.0001244767,0.00002036838,0.03195488,0.0003437356,0.00003185323,0.00007371443,0.0004267243,0.0002461785,0.0001452406,0.001301455,0.9652965,0.00003481864],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003155938,0.001153436,0.0001033351,0.001694893,0.0002641929,0.00001473773,0.9872322,0.0001835041,0.006197689],"genre_scores_gemma":[0.01109977,0.0006918718,0.0002326067,0.0003757002,0.0001053853,0.00006467872,0.9822662,0.00009063931,0.00507324],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09329513,"threshold_uncertainty_score":0.1855042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04335598721816944,"score_gpt":0.2981578349550917,"score_spread":0.2548018477369223,"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."}}