{"id":"W4379985861","doi":"10.1075/ll.22029.fed","title":"Turn-taking in the interactive Linguistic Landscape","year":2023,"lang":"en","type":"article","venue":"Linguistic Landscape An international journal","topic":"Language, Discourse, Communication Strategies","field":"Arts and Humanities","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of Alberta","funders":"Social Sciences and Humanities Research Council of Canada; Canada Foundation for Innovation","keywords":"Conversation; Interactivity; Semiotics; Linguistics; Conversation analysis; Turn-taking; Meaning (existential); Pairing; Mechanism (biology); Sociology; Communication; Computer science; Epistemology; Philosophy; Multimedia","routes":{"ca_aff":true,"ca_fund":true,"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":[0.005590855,0.0005114224,0.0004128475,0.002108474,0.004890875,0.008155126,0.001157045,0.0012739,0.006236541],"category_scores_gemma":[0.01062575,0.0003861343,0.0005226959,0.00120272,0.01821991,0.00810203,0.01037399,0.001660965,0.0006704614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002639691,"about_ca_system_score_gemma":0.001080265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001596925,"about_ca_topic_score_gemma":0.001620642,"domain_scores_codex":[0.9895968,0.008220193,0.0001423977,0.000583392,0.0007935178,0.000663813],"domain_scores_gemma":[0.9909489,0.006418106,0.000632492,0.0007858994,0.0005539722,0.000660668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001544523,0.00004407099,0.003983104,0.0002272711,0.00003030264,0.001481838,0.5401711,0.001467029,0.007070995,0.4096297,0.001679039,0.03406117],"study_design_scores_gemma":[0.00003903225,0.0001492764,0.005754153,0.0003805402,0.00006349041,0.001231323,0.4146442,0.006433317,0.004640699,0.4183099,0.1482545,0.00009954836],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5163508,0.00143022,0.174424,0.006104953,0.0002606376,0.0001883506,0.0001185119,0.0007018697,0.3004206],"genre_scores_gemma":[0.9927505,0.00008908357,0.00467266,0.00009612508,0.00001819782,0.000042062,0.00002151901,0.00007257875,0.002237217],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008155126,"threshold_uncertainty_score":0.0295676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05354177245520635,"score_gpt":0.3483638185530172,"score_spread":0.2948220460978108,"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."}}