{"id":"W4392284796","doi":"10.1080/0023656x.2024.2323046","title":"Why Windsor deindustrialized differently than Detroit","year":2024,"lang":"en","type":"article","venue":"Labor History","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Windsor; Deindustrialization; Underwriting; Industrialisation; Automotive industry; Economy; Atlanta; Business; Economic history; Economics; Geography; Engineering; Market economy; Archaeology; Finance","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":[0.0006013259,0.000107201,0.0001449714,0.000726955,0.005103272,0.002112172,0.0004932038,0.0005736989,0.004425333],"category_scores_gemma":[0.0009624922,0.0001343838,0.0001338032,0.001485672,0.001633609,0.001414512,0.001414057,0.0009785369,0.000489218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007306443,"about_ca_system_score_gemma":0.004955321,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6860107,"about_ca_topic_score_gemma":0.8899592,"domain_scores_codex":[0.9994277,0.00007920915,0.00001432083,0.0000890676,0.00008640569,0.0003032863],"domain_scores_gemma":[0.9991461,0.00005333648,0.0001795779,0.00003353723,0.0001966556,0.0003908056],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002736404,0.000129865,0.7228614,0.00009273175,0.00005000657,0.001117689,0.1776223,0.00007719838,0.002135287,0.01769194,0.02398557,0.05396235],"study_design_scores_gemma":[0.000007486541,0.00004265131,0.7875955,0.0001097181,0.000009896551,0.0001795978,0.148109,0.00004988279,0.0002307545,0.0003170192,0.06333142,0.00001698746],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9726992,0.0005911099,0.00004633701,0.00872155,0.00004873303,0.000008805551,0.0003460711,0.000003120745,0.01753509],"genre_scores_gemma":[0.9797463,0.0009146126,0.00008602063,0.001917517,0.00003897554,0.00001744242,0.0003094769,0.00001192358,0.0169578],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3139893,"threshold_uncertainty_score":0.6316768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0729760481332006,"score_gpt":0.3623173701674342,"score_spread":0.2893413220342336,"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."}}