{"id":"W2481561889","doi":"10.1075/slsi.25.11li","title":"Language and the body in the construction of units in Mandarin face-to-face interaction","year":2013,"lang":"en","type":"book-chapter","venue":"Studies in language and social interaction","topic":"Language, Discourse, Communication Strategies","field":"Arts and Humanities","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Mandarin Chinese; Body language; Conversation; Face (sociological concept); Resource (disambiguation); Computer science; Projection (relational algebra); Face-to-face; Linguistics; Psychology; Communication; Human–computer interaction; Epistemology; Philosophy; Algorithm","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":[0.001060173,0.000435691,0.0002338387,0.0009458213,0.002453796,0.003642145,0.0006573538,0.0009521763,0.002723173],"category_scores_gemma":[0.002082515,0.0002179913,0.0002385806,0.0006262255,0.008607023,0.003301976,0.00310859,0.0008508579,0.0005069067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001006851,"about_ca_system_score_gemma":0.0008167124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003760651,"about_ca_topic_score_gemma":0.005999656,"domain_scores_codex":[0.9989028,0.0006693341,0.00003256841,0.0001211652,0.0001671297,0.0001068511],"domain_scores_gemma":[0.9993231,0.000471597,0.00005904666,0.00003988261,0.00004524062,0.00006110731],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002012771,0.00004542935,0.004413306,0.0003987276,0.0000173357,0.002213652,0.6930943,0.0004610702,0.02607595,0.1346434,0.001377243,0.1370583],"study_design_scores_gemma":[0.00004480428,0.000492218,0.07666878,0.002251113,0.0001053068,0.006023271,0.5594622,0.00487664,0.02260171,0.1019539,0.2252882,0.0002318785],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6271943,0.008715198,0.02852766,0.001622102,0.0001332892,0.00007183648,0.0000352672,0.0001539274,0.3335463],"genre_scores_gemma":[0.9831435,0.001023058,0.005652306,0.0001281108,0.00003119265,0.00004775446,0.00002507753,0.00007102743,0.009878006],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003760651,"threshold_uncertainty_score":0.009109974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06864976460568556,"score_gpt":0.3536226459970568,"score_spread":0.2849728813913712,"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."}}