{"id":"W2184224772","doi":"10.2196/medinform.4797","title":"Resident Use of Text Messaging for Patient Care: Ease of Use or Breach of Privacy?","year":2015,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute","keywords":"Short Message Service; Text messaging; Confidentiality; Paging; Internet privacy; Medicine; Usability; Protected health information; Identifier; Credential; Family medicine; Medical emergency; Computer science; Computer security; Nursing; Public health","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":[],"consensus_categories":[],"category_scores_codex":[0.0009420622,0.0001453093,0.0005494916,0.0001660113,0.0001373392,0.00000390863,0.0002680901,0.0003073604,0.0001397889],"category_scores_gemma":[0.003457949,0.0001064459,0.00007928604,0.0002987486,0.0001553476,0.0002886081,0.0002052006,0.0004135369,0.00001384275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001513947,"about_ca_system_score_gemma":0.003814797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005738169,"about_ca_topic_score_gemma":0.0001030307,"domain_scores_codex":[0.9955738,0.0001641619,0.002751443,0.0001034622,0.0009217659,0.0004853961],"domain_scores_gemma":[0.9940445,0.001767639,0.001471047,0.0006214135,0.001097759,0.0009976663],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002273145,0.001003754,0.05321339,0.05111978,0.00009257659,0.000003067761,0.2557077,0.00007417397,0.00002444442,0.01736587,0.4955829,0.1235392],"study_design_scores_gemma":[0.005748076,0.001361436,0.006293498,0.002772325,0.00007963478,0.000004981541,0.04837703,0.004804674,0.0002698738,0.0002719038,0.9297564,0.0002601418],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9802638,0.0001811242,0.006227575,0.001115027,0.0004312638,0.009893186,0.0004808134,0.00007125432,0.001335939],"genre_scores_gemma":[0.9648736,0.0003026791,0.02438669,0.003614772,0.0001123618,0.005963834,0.0002454641,0.00003922009,0.0004613879],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4341736,"threshold_uncertainty_score":0.6767286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1338799490278076,"score_gpt":0.4610658875412161,"score_spread":0.3271859385134085,"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."}}