{"id":"W3033417012","doi":"","title":"Mutations of Vancouver's Chinatown: Spatial redistribution and new territorial logic's","year":2008,"lang":"en","type":"article","venue":"Publications Pimido","topic":"Urbanization and City Planning","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Chinatown; Redistribution (election); Geography; Genealogy; Computer science; History; Political science; Archaeology; Law","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001614609,0.00005657594,0.000084857,0.00009626622,0.0006517649,0.0000433195,0.0001310843,0.00007729264,0.0002295467],"category_scores_gemma":[0.0007736655,0.00006101898,0.00002668537,0.0004735355,0.0002113843,0.0003365314,0.00002246761,0.00007054253,0.00000715346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005536777,"about_ca_system_score_gemma":0.0003798169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003136696,"about_ca_topic_score_gemma":0.002640464,"domain_scores_codex":[0.9992458,0.00005828547,0.0001819934,0.0001395973,0.0002395051,0.0001348155],"domain_scores_gemma":[0.9993337,0.0000685678,0.000115192,0.0001181479,0.0002301233,0.0001342644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001091306,0.0001686808,0.04199081,0.000005851771,0.00002464297,6.723192e-7,0.01353282,0.00002782434,0.0001552738,0.6363818,0.3031776,0.004523102],"study_design_scores_gemma":[0.0006455384,0.00003919963,0.09755307,0.000009371164,0.00002864392,0.000004069346,0.001700741,0.0003676152,0.0002043688,0.01459913,0.8846446,0.0002036608],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1577544,0.0005179968,0.2992783,0.06015268,0.007628085,0.001784212,0.0004466841,0.001286297,0.4711513],"genre_scores_gemma":[0.9957771,0.00003325782,0.001052344,0.0000687314,0.0006637598,0.00001126268,0.0001484764,0.000004588548,0.002240472],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8380227,"threshold_uncertainty_score":0.5012915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04259279531687485,"score_gpt":0.2922411999079612,"score_spread":0.2496484045910864,"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."}}