{"id":"W4390974049","doi":"10.5267/j.ijdns.2023.11.004","title":"The impact of using WhatsApp on the team’s communication, employee performance and data confidentiality","year":2024,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Organizational and Employee Performance","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Confidentiality; Encryption; Task (project management); Information exchange; Descriptive statistics; Computer science; Test (biology); Psychology; Internet privacy; Knowledge management; Computer security; Engineering; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.003074052,0.00007017727,0.00008202445,0.00006455686,0.0004112359,0.0009450864,0.006302638,0.00001380581,0.000004508347],"category_scores_gemma":[0.0001353841,0.0000350941,0.00001598745,0.0004296003,0.0005619755,0.003461731,0.002377215,0.0001631522,0.000001379669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002982796,"about_ca_system_score_gemma":0.0003976139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004402627,"about_ca_topic_score_gemma":0.00000694469,"domain_scores_codex":[0.9987354,0.00005052634,0.0003017841,0.0002004029,0.0005864907,0.0001253492],"domain_scores_gemma":[0.9981132,0.0004183698,0.0001844387,0.0008809613,0.0003535345,0.00004946362],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002572609,0.000220914,0.3552504,0.00006574077,0.0009809537,0.00002086243,0.004147914,0.02039001,0.002612388,0.1353316,0.1434295,0.3372925],"study_design_scores_gemma":[0.0001149086,0.00007901713,0.08554653,0.0002948871,0.00001291087,0.000289786,0.00004817241,0.9059571,0.000141816,0.003039122,0.004386944,0.00008880732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9680107,0.002723382,0.02422874,0.003868614,0.0008732067,0.00007228234,0.00006111929,0.00001107653,0.0001508617],"genre_scores_gemma":[0.9944896,0.003099775,0.002101165,0.00008677083,0.0001999511,1.870327e-7,0.000006427508,0.000002877304,0.00001325458],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8855671,"threshold_uncertainty_score":0.9990737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06154433251331629,"score_gpt":0.3608777625044033,"score_spread":0.299333429991087,"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."}}