{"id":"W2014653992","doi":"10.1111/j.1468-2427.2005.00608.x","title":"Introduction to a Debate on Migration, Diversity, Multiculturalism, Citizenship: Challenges for Cities in Europe and North America","year":2005,"lang":"en","type":"article","venue":"International Journal of Urban and Regional Research","topic":"Cross-Border Cooperation and Integration","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"German; Multiculturalism; Citizenship; Library science; Diversity (politics); Citation; Political science; Media studies; Sociology; History; Law; Computer science","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":[0.00434366,0.00083531,0.0007745679,0.00125479,0.008022081,0.01150392,0.001812993,0.01604862,0.01374426],"category_scores_gemma":[0.006129613,0.0003584826,0.0009615787,0.002329384,0.0107793,0.009706322,0.006108776,0.01716421,0.001815904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003866176,"about_ca_system_score_gemma":0.004946925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01224626,"about_ca_topic_score_gemma":0.01869642,"domain_scores_codex":[0.9979956,0.0008206086,0.0001138887,0.0003949803,0.0004084104,0.0002665688],"domain_scores_gemma":[0.9919506,0.005861797,0.0002419849,0.0002574988,0.001034181,0.0006539179],"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":[0.00004686364,0.00004463473,0.0005026663,0.0004458846,0.00001143698,0.0001503972,0.01016123,0.0001497233,0.0002948492,0.3429082,0.6151563,0.03012775],"study_design_scores_gemma":[0.00001229934,0.00001672167,0.0007962168,0.000770211,0.000007037503,0.00007765836,0.005756467,0.00007679762,0.0000466823,0.02671665,0.9657039,0.00001946895],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.002915891,0.0530872,0.002098758,0.8351673,0.05946818,0.000029642,0.0002252445,0.00004488534,0.04696297],"genre_scores_gemma":[0.08546382,0.0433854,0.004433839,0.6842958,0.09217376,0.0002273597,0.0003153018,0.0002281116,0.08947668],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.01604862,"threshold_uncertainty_score":0.04597914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1268639609449669,"score_gpt":0.405312061195655,"score_spread":0.2784481002506882,"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."}}