{"id":"W2961770978","doi":"10.1093/pastj/gtz017","title":"A Microhistory of the Global Empire of Cotton: Ivanovo, The ‘Russian Manchester’*","year":2019,"lang":"en","type":"article","venue":"Past & Present","topic":"Historical Studies and Socio-cultural Analysis","field":"Arts and Humanities","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Serfdom; History; Economic history","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006822759,0.0001007017,0.0002252517,0.000007486056,0.0005568031,0.00001745284,0.000317129,0.00002550035,0.0005967868],"category_scores_gemma":[0.000004409288,0.00004496619,0.0002800431,0.00005285386,0.0003699945,0.00003625935,0.0001487119,0.00007854531,0.00004092478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002998323,"about_ca_system_score_gemma":0.00001296837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001126477,"about_ca_topic_score_gemma":0.0008254275,"domain_scores_codex":[0.9992025,0.00006042783,0.0002276742,0.0001254695,0.0002412989,0.000142649],"domain_scores_gemma":[0.9994423,0.00003556626,0.0001549501,0.00028327,0.00005760983,0.00002624447],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008854039,0.0004872218,0.04942026,0.0003558841,0.0009921836,0.00000289308,0.4993783,0.00008924949,0.0002990055,0.2389933,0.2067265,0.003166652],"study_design_scores_gemma":[0.0001427748,0.00003778663,0.00622753,0.00002497321,0.00008392691,4.916158e-7,0.005664285,0.00001373022,0.00003156567,0.0009106927,0.9867775,0.00008472452],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8679368,0.002430951,0.000003166451,0.06591231,0.0008283575,0.0003232779,0.00004978339,0.00001646284,0.06249883],"genre_scores_gemma":[0.9795665,0.00003560844,0.000004959732,0.0001704557,0.0003479939,0.000007696196,0.000001334655,0.000004451441,0.01986096],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.780051,"threshold_uncertainty_score":0.6534396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01548683209554559,"score_gpt":0.2078994557728085,"score_spread":0.1924126236772629,"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."}}