{"id":"W1966551893","doi":"10.1111/1468-0289.00168","title":"Manufacturing quality in the pre‐industrial age: finding value in diversity","year":2000,"lang":"en","type":"article","venue":"The Economic History Review","topic":"Historical Economic and Legal Thought","field":"Social Sciences","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Pace; Diversity (politics); Quality (philosophy); Sorting; Scale (ratio); Excellence; Work (physics); Value (mathematics); Marketing; Industrial organization; Business; Computer science; Economics; Operations management; Engineering; Political science; Geography; Law; Mechanical engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003482966,0.0001637355,0.0003298749,0.002612982,0.003006755,0.005985891,0.0005195975,0.001616427,0.002112971],"category_scores_gemma":[0.004864095,0.0001556528,0.0001773519,0.003390284,0.01787233,0.005663285,0.002135516,0.002141551,0.0002496685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008566524,"about_ca_system_score_gemma":0.004648628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009003612,"about_ca_topic_score_gemma":0.01295219,"domain_scores_codex":[0.9974637,0.001304722,0.00007899553,0.0002215729,0.000615474,0.0003155876],"domain_scores_gemma":[0.9971077,0.001446147,0.0004287273,0.0001781643,0.0006230876,0.0002161522],"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":[0.00003407165,0.00003395506,0.002985979,0.0003071183,0.00001809148,0.0002043648,0.009693787,0.0003876775,0.0001407713,0.9102253,0.007826654,0.06814227],"study_design_scores_gemma":[0.00002490277,0.0001042065,0.01955265,0.001283267,0.00001551219,0.0003140372,0.01164263,0.0002762887,0.0002380654,0.4127984,0.5537286,0.00002144289],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1018271,0.4608712,0.004032214,0.1410224,0.0008104047,0.00002786966,0.00006249969,0.00001575695,0.2913306],"genre_scores_gemma":[0.8148805,0.1637166,0.0008264233,0.007755303,0.001381591,0.00002179513,0.00002270385,0.00001087882,0.0113843],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009003612,"threshold_uncertainty_score":0.06215483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1581810201227574,"score_gpt":0.3264754691074098,"score_spread":0.1682944489846523,"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."}}