{"id":"W4388869859","doi":"10.21105/joss.05497","title":"OpenTera: A Framework for TelehealthApplications","year":2023,"lang":"en","type":"article","venue":"The Journal of Open Source Software","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; AGE-WELL","keywords":"Telehealth; Data collection; Software deployment; Computer science; Wearable computer; Biometrics; Authentication (law); Videoconferencing; Telemedicine; Field (mathematics); Data science; Human–computer interaction; Wearable technology; Data access; Health care; World Wide Web; Multimedia; Database; Artificial intelligence; Computer security; Software engineering; Embedded system","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.00294848,0.0001145162,0.000270422,0.00009853149,0.0005106901,0.0002961031,0.004288694,0.00006725788,0.00001198089],"category_scores_gemma":[0.0005766744,0.00006766348,0.0001312747,0.0008093299,0.00005339479,0.0006586392,0.0007523964,0.000279519,0.0001036466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000507816,"about_ca_system_score_gemma":0.0002122042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002661513,"about_ca_topic_score_gemma":0.000002578323,"domain_scores_codex":[0.9986106,0.0001265444,0.0005159298,0.0001544575,0.000307279,0.0002851606],"domain_scores_gemma":[0.9968973,0.001401614,0.0004661998,0.0007889756,0.0003324728,0.0001133803],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005005992,0.0004407006,0.0374767,0.0005264589,0.0003984967,0.00001680302,0.03359989,0.0084333,0.000103013,0.02557776,0.2628571,0.6300692],"study_design_scores_gemma":[0.002854184,0.001255803,0.04037361,0.001014978,0.0001237803,0.0007867942,0.002868785,0.007958388,0.0006029336,0.2177184,0.7236791,0.0007632104],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02667678,0.0001721578,0.9649002,0.006814709,0.0004799282,0.0007812738,0.000005367544,0.0001241274,0.00004548857],"genre_scores_gemma":[0.6247255,0.0002892708,0.3699109,0.002533734,0.0007669213,0.0001968759,0.000004962129,0.00005819125,0.001513703],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.629306,"threshold_uncertainty_score":0.7969532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04303871831525866,"score_gpt":0.3530332805725033,"score_spread":0.3099945622572446,"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."}}