{"id":"W3034687283","doi":"10.1177/0165551520929931","title":"From words to connections: Word use similarity as an honest signal conducive to employees’ digital communication","year":2020,"lang":"en","type":"article","venue":"Journal of Information Science","topic":"Knowledge Management and Sharing","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Homophily; Intranet; Similarity (geometry); Computer science; Word (group theory); Position (finance); Semantic similarity; Knowledge management; World Wide Web; Natural language processing; The Internet; Artificial intelligence; Psychology; Linguistics; Social psychology; Business","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":[0.001790518,0.0003238271,0.000351811,0.001929943,0.0009704941,0.004992485,0.0003523254,0.001038625,0.005066669],"category_scores_gemma":[0.02736258,0.0002126052,0.0002912956,0.001733908,0.002261885,0.003964104,0.002761398,0.0009825886,0.000598334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004377974,"about_ca_system_score_gemma":0.0005026363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008621591,"about_ca_topic_score_gemma":0.0008159583,"domain_scores_codex":[0.9970732,0.001382502,0.0002403002,0.0004343341,0.0006094505,0.0002602885],"domain_scores_gemma":[0.9599832,0.02877232,0.006643916,0.001234855,0.001679693,0.001686027],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001042171,0.0003642766,0.7779226,0.0005524301,0.0002442449,0.00105246,0.1322735,0.0008822787,0.01686466,0.00969679,0.001082579,0.05802206],"study_design_scores_gemma":[0.00002850542,0.0005940257,0.8817326,0.0001544896,0.0001870034,0.0008861738,0.0900016,0.004207102,0.004037751,0.01391685,0.004107051,0.0001467391],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939434,0.00008100399,0.001478018,0.0002482067,0.00001366478,0.00001160393,0.00005529363,0.00001760847,0.004151179],"genre_scores_gemma":[0.9991502,0.00002749358,0.000496243,0.00002628991,0.00001448414,0.00001031153,0.00004136923,0.000008401222,0.0002251029],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005066669,"threshold_uncertainty_score":0.01694965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07920571504567828,"score_gpt":0.3526030939106429,"score_spread":0.2733973788649646,"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."}}