{"id":"W2996023428","doi":"10.2196/15494","title":"Mutual-Aid Mobile App for Emergency Care: Feasibility Study","year":2019,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cronbach's alpha; Likert scale; Descriptive statistics; Government (linguistics); Psychology; Medical education; Health care; Quality (philosophy); IBM; Sample (material); Applied psychology; Medical emergency; Nursing; Medicine; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01187793,0.0009261871,0.000692066,0.001261766,0.001488841,0.001157128,0.0009380679,0.001594616,0.00414182],"category_scores_gemma":[0.01250717,0.000683732,0.001054217,0.000490074,0.000922373,0.002127724,0.001608937,0.001294975,0.001034209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007656468,"about_ca_system_score_gemma":0.004370867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001348984,"about_ca_topic_score_gemma":0.002122701,"domain_scores_codex":[0.9946956,0.003052829,0.0003994883,0.0004171509,0.0007278843,0.0007071331],"domain_scores_gemma":[0.9942304,0.002534835,0.0004374031,0.0004113933,0.001370798,0.001015204],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0117438,0.317876,0.3390442,0.008058189,0.0004575851,0.01839601,0.05946387,0.001443772,0.02370575,0.00229507,0.009943677,0.207572],"study_design_scores_gemma":[0.009768935,0.367968,0.4816552,0.001612554,0.0007672994,0.01103481,0.08247472,0.006503831,0.007995797,0.001051199,0.02874811,0.0004194371],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9756777,0.0001895817,0.002368932,0.0004522813,0.00005242056,0.01922856,0.0002320889,0.00002825615,0.001770134],"genre_scores_gemma":[0.9407364,0.0009297537,0.01525563,0.001226683,0.0001263808,0.03955631,0.000468066,0.00002047299,0.001680347],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01187793,"threshold_uncertainty_score":0.06281728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1589810725549163,"score_gpt":0.5865405138027113,"score_spread":0.427559441247795,"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."}}