{"id":"W2578150167","doi":"10.7202/1038557ar","title":"Ségrégation raciale et géographique : le cas de Newark au New Jersey, 1937-1967","year":2016,"lang":"fr","type":"article","venue":"Cahiers d histoire","topic":"Race, History, and American Society","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Humanities; Sociology; Ethnology; Art; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.000554226,0.000138864,0.0002554866,0.001729296,0.007858328,0.003308796,0.0009955087,0.0005295718,0.00553306],"category_scores_gemma":[0.0008971026,0.0002506891,0.0001592569,0.003700691,0.003864694,0.001745518,0.00287158,0.001639002,0.0003772927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01517037,"about_ca_system_score_gemma":0.00637844,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.7989769,"about_ca_topic_score_gemma":0.9269101,"domain_scores_codex":[0.9993497,0.0001110797,0.00002153139,0.0001045156,0.0001263238,0.0002869158],"domain_scores_gemma":[0.9993935,0.0001140018,0.000151959,0.00004714663,0.000138448,0.0001549948],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0002605076,0.0002945476,0.4009524,0.0001336161,0.00005305584,0.002970353,0.4716815,0.0003168798,0.002618197,0.0399153,0.01730022,0.06350345],"study_design_scores_gemma":[0.000006967872,0.00004336958,0.6744359,0.00009149488,0.00003488358,0.0002915985,0.2180279,0.0001013874,0.0003992328,0.0006218466,0.1059143,0.0000312301],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9726505,0.0006103934,0.0001473996,0.00255338,0.00005265381,0.00001484755,0.0003605596,0.00001305207,0.02359708],"genre_scores_gemma":[0.9835237,0.0007398739,0.0002264568,0.000305458,0.0000320461,0.00003828908,0.0005139898,0.00001345221,0.01460688],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7989769,"threshold_uncertainty_score":0.4044139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01232146763109655,"score_gpt":0.2597089012517713,"score_spread":0.2473874336206747,"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."}}