{"id":"W2615406299","doi":"","title":"Crisis warning signs in mHealth for military veterans: a collaborative design approach","year":2016,"lang":"en","type":"article","venue":"International Conference on Information Systems for Crisis Response and Management","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"mHealth; Warning signs; Computer science; Computer security; Medicine; Engineering; Nursing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04827745,0.001202291,0.001096415,0.002513024,0.003715196,0.005733728,0.002106075,0.002182272,0.005607898],"category_scores_gemma":[0.07821564,0.001104471,0.001735705,0.001000914,0.001886562,0.003047254,0.004335047,0.00156543,0.0005765101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00378284,"about_ca_system_score_gemma":0.008303424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002566607,"about_ca_topic_score_gemma":0.003484111,"domain_scores_codex":[0.9526968,0.0395638,0.002416293,0.001675034,0.002675266,0.0009727074],"domain_scores_gemma":[0.9211981,0.06524438,0.002403829,0.002737275,0.006964019,0.001452328],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.005641526,0.02194936,0.03775702,0.01078495,0.001207051,0.0007947459,0.2232988,0.01631781,0.01635506,0.03405445,0.003798621,0.6280406],"study_design_scores_gemma":[0.02114626,0.1013347,0.07023,0.01407502,0.01109604,0.001595907,0.3315325,0.1805218,0.07444403,0.07342736,0.1190345,0.00156193],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6480269,0.0007226252,0.2937555,0.002040687,0.000244046,0.03430096,0.0002926883,0.0005250441,0.02009153],"genre_scores_gemma":[0.587791,0.0003681202,0.3875776,0.0003430534,0.00003010341,0.02158425,0.00009577517,0.00005832789,0.002151777],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04827745,"threshold_uncertainty_score":0.2553186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05836766546162819,"score_gpt":0.3439290766955029,"score_spread":0.2855614112338747,"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."}}