{"id":"W3098390954","doi":"10.6000/1929-4409.2020.09.83","title":"Linguocultural Analysis of the Most Common Greetings in the Russian, Tatar and Chinese Languages","year":2020,"lang":"en","type":"article","venue":"International Journal of Criminology and Sociology","topic":"Cultural, Linguistic, Economic Studies","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Kazan Federal University","keywords":"Tatar; Linguistics; Constructive; Clan; Originality; Psychology; Interpretation (philosophy); Sociology; Social psychology; Philosophy; Computer science; Process (computing); Anthropology; Creativity","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":[0.001247715,0.0001956089,0.0002444551,0.002768486,0.001983281,0.001359329,0.0003014285,0.0002207263,0.001401679],"category_scores_gemma":[0.002330836,0.0001087385,0.0002658265,0.002608935,0.001200099,0.0006087959,0.001067405,0.0004914794,0.0001444341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008787283,"about_ca_system_score_gemma":0.000750487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005930704,"about_ca_topic_score_gemma":0.01213784,"domain_scores_codex":[0.9990255,0.0004437045,0.0001233897,0.0001243352,0.000147299,0.0001357476],"domain_scores_gemma":[0.9975758,0.001082564,0.0005166593,0.0001697435,0.0004537221,0.0002014566],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.000455872,0.0001506502,0.2719779,0.0005305251,0.00009673464,0.004418096,0.6185918,0.0001511389,0.01759658,0.007469964,0.001029995,0.07753076],"study_design_scores_gemma":[0.00000418928,0.0001271949,0.6163206,0.00008699929,0.00004516275,0.001848677,0.372331,0.000227908,0.001460983,0.0003269333,0.007192581,0.00002789639],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963918,0.0001702969,0.00007528169,0.00003244954,0.000009256448,0.000007045997,0.00002827388,0.000001641104,0.003283864],"genre_scores_gemma":[0.998975,0.0001785426,0.0001410219,0.0000107965,0.000005223039,0.000006566589,0.00007569564,0.000005513431,0.0006015741],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005930704,"threshold_uncertainty_score":0.01179236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05579761448381216,"score_gpt":0.3671461853404919,"score_spread":0.3113485708566797,"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."}}