{"id":"W2992451855","doi":"","title":"Linguistic Landscape of China—A Case Study of Shop Signs in Beijing","year":2013,"lang":"en","type":"article","venue":"Studies in literature and language","topic":"Swearing, Euphemism, Multilingualism","field":"Social Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Beijing; China; Linguistic landscape; Sign (mathematics); Linguistics; Focus (optics); History; Political science; Philosophy; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004920933,0.0001116944,0.0003162761,0.0001549588,0.0000846882,0.00002871502,0.0001054348,0.00007494719,0.00002706165],"category_scores_gemma":[0.001166376,0.00009284309,0.00002574023,0.0004313042,0.0001594989,0.0000844336,0.00009662452,0.000199499,4.15026e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002128385,"about_ca_system_score_gemma":0.00001986108,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007757143,"about_ca_topic_score_gemma":0.01384591,"domain_scores_codex":[0.9989861,0.0001452519,0.000297084,0.0001994564,0.0001684469,0.0002037062],"domain_scores_gemma":[0.9993401,0.000272291,0.0001006032,0.0001481069,0.0001039401,0.00003502518],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00000663932,0.0001322344,0.08175468,0.0000966689,0.00002777948,0.0008782766,0.9156842,0.00000446082,0.0002603057,0.0001456555,0.00003236731,0.0009767868],"study_design_scores_gemma":[0.0008976024,0.0001604385,0.008682103,0.0003993798,0.0000211184,0.00002192361,0.9893147,0.00003780901,0.0000638221,0.0001522338,0.00009207091,0.0001567742],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9801061,0.01380681,3.041023e-7,0.00002362446,0.0001623367,0.0003526506,0.000004244739,0.00001360745,0.005530315],"genre_scores_gemma":[0.9992988,0.0001528748,0.000112186,0.0000206091,0.0001574631,0.00002017055,0.000001369122,0.000007587986,0.0002289566],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07363058,"threshold_uncertainty_score":0.9988503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02555523670420965,"score_gpt":0.3770613848365428,"score_spread":0.3515061481323332,"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."}}