{"id":"W4301318044","doi":"10.46692/9781447327899.001","title":"Introduction: why Detroit matters","year":2017,"lang":"en","type":"other","venue":"","topic":"Political and Economic history of UK and US","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00188146,0.0004782838,0.0004127149,0.0006641918,0.006811128,0.007986272,0.001594155,0.007422504,0.2398719],"category_scores_gemma":[0.007151681,0.0003560605,0.0003881754,0.001070917,0.001895645,0.004950839,0.003405573,0.006802484,0.07194328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0058424,"about_ca_system_score_gemma":0.008984839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07760099,"about_ca_topic_score_gemma":0.1198635,"domain_scores_codex":[0.9980118,0.0003750825,0.00007691617,0.0004258749,0.0006166762,0.0004935234],"domain_scores_gemma":[0.9949526,0.0005343122,0.0001529388,0.0001797624,0.001517657,0.002662768],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00000463005,0.000008421681,0.0004090068,0.00003096487,0.000001275578,0.000106982,0.0002601822,0.000002102449,0.00003734393,0.002134541,0.9916759,0.005328609],"study_design_scores_gemma":[0.000003060538,0.000004622448,0.001540009,0.0001048483,0.000001255706,0.0001198646,0.0009846961,0.000008715487,0.0000308908,0.0003390895,0.9968557,0.000007283444],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.003717907,0.006643839,0.0002405077,0.668873,0.04094821,0.00009059884,0.001819543,0.0003212474,0.2773452],"genre_scores_gemma":[0.01814566,0.003472111,0.0003540173,0.4041068,0.008589514,0.000172978,0.001073725,0.0003064401,0.5637788],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.2398719,"threshold_uncertainty_score":0.8024516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01862285811919348,"score_gpt":0.2668986202368154,"score_spread":0.248275762117622,"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."}}