{"id":"W1589096524","doi":"","title":"Was Canadian Manufacturing Inefficient before WWI? The Case of the Cotton Textile Industry, 1870-1910","year":2011,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Textile industry; Textile; Productivity; Manufacturing; Agricultural economics; Economics; Total factor productivity; Business; Commerce; Economy; Marketing; Economic growth; Geography; Political science; Law","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":[0.001893162,0.0003648736,0.000455521,0.003076845,0.01168697,0.004979464,0.0008369033,0.001567862,0.003452793],"category_scores_gemma":[0.005330734,0.0002604922,0.0004347492,0.007574101,0.006617161,0.001700768,0.001092423,0.001855524,0.0002892232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.111588,"about_ca_system_score_gemma":0.05456472,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9939278,"about_ca_topic_score_gemma":0.9949524,"domain_scores_codex":[0.9980483,0.00009702582,0.00003385534,0.0001863246,0.0005476342,0.00108683],"domain_scores_gemma":[0.997279,0.0003473221,0.0003187277,0.0001377459,0.001586704,0.000330522],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0004285345,0.00004601949,0.1698642,0.0003007361,0.000213096,0.004733974,0.0264003,0.005450735,0.001025494,0.6537996,0.05715755,0.08057994],"study_design_scores_gemma":[0.00004778182,0.00004082532,0.7172692,0.0004370857,0.0002372284,0.0006045673,0.03213337,0.001729369,0.001292043,0.02724845,0.2187424,0.0002177065],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6703104,0.01043526,0.0006048272,0.05098222,0.0001426632,0.00002911905,0.002604329,0.00003048677,0.2648606],"genre_scores_gemma":[0.9800427,0.004026333,0.0002301944,0.001569897,0.00007609945,0.00000509926,0.0004768993,0.0000159504,0.01355681],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.111588,"threshold_uncertainty_score":0.8096313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04725821766137355,"score_gpt":0.2628814005552425,"score_spread":0.2156231828938689,"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."}}