{"id":"W2940305191","doi":"10.1002/9781118568446.eurs0204","title":"Migration, Gender, Cities","year":2019,"lang":"en","type":"other","venue":"The Wiley Blackwell Encyclopedia of Urban and Regional Studies","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Gentrification; Citizenship; Scholarship; Sociology; Gender studies; Inequality; Politics; Political science; Economic growth","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002881171,0.000225642,0.0003750426,0.0001053779,0.0002643706,0.00002168347,0.0002487123,0.0001829786,0.000226995],"category_scores_gemma":[0.00008229275,0.0001464289,0.0000974184,0.000161669,0.001524173,0.000041542,0.00006738972,0.0001446282,0.00005405465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003031605,"about_ca_system_score_gemma":0.0001512288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001241485,"about_ca_topic_score_gemma":0.01234284,"domain_scores_codex":[0.9987026,0.0001693066,0.0002402885,0.0002368143,0.0004372628,0.0002137547],"domain_scores_gemma":[0.9990758,0.000240377,0.0002917287,0.00021854,0.0001264468,0.00004707798],"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":[0.000006544855,0.00001668457,0.0006524012,0.00008755022,0.0001751913,5.814993e-7,0.03246189,0.000002707152,1.785673e-7,0.04539578,0.9208686,0.0003319064],"study_design_scores_gemma":[0.0001337669,0.00001886651,0.00006561078,0.0001902167,0.00007382863,4.615816e-7,0.01688137,0.00001429397,1.551487e-7,0.00166979,0.9807675,0.000184087],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0004464666,0.1783251,0.000006791211,0.0025861,0.0006064367,0.0004124724,0.00005039598,0.00007328443,0.8174929],"genre_scores_gemma":[0.0002725158,0.435469,0.00002919115,0.0002232818,0.0004993431,0.00001050665,0.00001372349,0.00004698065,0.5634354],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2571439,"threshold_uncertainty_score":0.6887596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03222876184655762,"score_gpt":0.2839080831496301,"score_spread":0.2516793213030725,"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."}}