{"id":"W4391220998","doi":"10.2196/51260","title":"Connecting actors with the introduction of mobile technology in healthcare practice placements (4D Project): Protocol for a mixed methods study (Preprint)","year":2023,"lang":"en","type":"article","venue":"JMIR Research Protocols","topic":"Mobile Learning in Education","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Preprint; Protocol (science); Health care; Computer science; Medicine; Medical education; World Wide Web; Political science; Alternative medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"qualitative","genre":"protocol","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"design_other","genre":"protocol","about_ca_system":false,"about_ca_topic":false,"confidence":"medium","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1039689,0.004500718,0.004886359,0.004960757,0.009397779,0.005775844,0.00392754,0.01069235,0.09493268],"category_scores_gemma":[0.1502848,0.005676143,0.003835678,0.004461349,0.005587267,0.004018896,0.005194834,0.009587585,0.02009592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007490348,"about_ca_system_score_gemma":0.0261683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00523714,"about_ca_topic_score_gemma":0.006109459,"domain_scores_codex":[0.9154962,0.05562942,0.01459848,0.004661017,0.005155515,0.004459248],"domain_scores_gemma":[0.8958867,0.05493189,0.01022091,0.01624648,0.01828362,0.004430462],"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":[0.2509178,0.03663639,0.007284799,0.08890215,0.001284064,0.001382274,0.0636752,0.007444573,0.009760174,0.0459192,0.08901391,0.3977795],"study_design_scores_gemma":[0.3035414,0.05316209,0.03134463,0.0439645,0.002266535,0.0003321587,0.04371905,0.01146024,0.02304577,0.04811812,0.4369799,0.00206563],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"protocol","genre_gemma":"protocol","genre_scores_codex":[0.006145366,0.0001420531,0.008185265,0.000409026,0.0004116179,0.9800214,0.002299716,0.0001554266,0.002230135],"genre_scores_gemma":[0.0009974162,0.00001815418,0.00225828,0.00003353212,0.000012021,0.9964561,0.00004604378,0.000004366242,0.0001740421],"genre_candidate":"protocol","genre_consensus":"protocol","teacher_disagreement_score":0.1039689,"threshold_uncertainty_score":0.5498468,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1969921251536061,"score_gpt":0.6237116989505829,"score_spread":0.4267195737969767,"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."}}