{"id":"W4383376996","doi":"10.5430/wjel.v13n7p18","title":"Linguistic Landscape and Markedness Conceptualization in Commercial Ads","year":2023,"lang":"en","type":"article","venue":"World Journal of English Language","topic":"Swearing, Euphemism, Multilingualism","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universitas Mataram","keywords":"Foregrounding; Markedness; Linguistics; Conceptualization; Linguistic landscape; Context (archaeology); Signage; Context analysis; Computer science; Sociology; Psychology; Advertising; Geography; Business","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001905408,0.0002836512,0.00017314,0.002546248,0.002497,0.006609494,0.0004968139,0.0006865721,0.003015022],"category_scores_gemma":[0.003182438,0.0001921095,0.0001952708,0.001614846,0.009514102,0.005558769,0.002844729,0.0009424601,0.0001876272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002340962,"about_ca_system_score_gemma":0.0005166912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002208292,"about_ca_topic_score_gemma":0.001977398,"domain_scores_codex":[0.9981694,0.001223653,0.00007413011,0.0001652421,0.0002473694,0.0001201379],"domain_scores_gemma":[0.9980425,0.001102692,0.0003829775,0.0001331774,0.0002023525,0.0001363171],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001914745,0.0000901744,0.02125781,0.000352562,0.00002418651,0.00132259,0.5844373,0.0003465184,0.01010245,0.3415334,0.0008562659,0.03948533],"study_design_scores_gemma":[0.00003422798,0.0002944845,0.08473698,0.0004391841,0.00007194503,0.002014742,0.7604131,0.002697463,0.002781704,0.07407434,0.0723417,0.0001002165],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.847618,0.001353952,0.007753869,0.001305143,0.00005045473,0.00004816601,0.00004998556,0.000035756,0.1417847],"genre_scores_gemma":[0.9986332,0.00008754043,0.0005559539,0.0000399151,0.00001054744,0.00001096269,0.0000100101,0.000007352493,0.0006444847],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006609494,"threshold_uncertainty_score":0.01698494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01954918408697955,"score_gpt":0.3277408906550665,"score_spread":0.308191706568087,"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."}}