{"id":"W7015064840","doi":"","title":"The Response of Mobile Applications to Crisis in Canada","year":2020,"lang":"en","type":"dissertation","venue":"MacSphere (McMaster University)","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Order (exchange); Key (lock); Mobile apps; Mobile device; Pandemic; Health care; Coronavirus disease 2019 (COVID-19); mHealth","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.008701191,0.0003883624,0.00046241,0.002238906,0.007395379,0.0082413,0.001052324,0.001339811,0.004029717],"category_scores_gemma":[0.03174897,0.0002933826,0.0004756056,0.004099443,0.002162943,0.002271387,0.00300456,0.001574035,0.0006642197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03633012,"about_ca_system_score_gemma":0.137254,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8558167,"about_ca_topic_score_gemma":0.9213127,"domain_scores_codex":[0.9954243,0.001466198,0.000273236,0.0002431211,0.001957152,0.0006359639],"domain_scores_gemma":[0.9856424,0.004967022,0.0004616498,0.0001990549,0.007659023,0.001070968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005591516,0.00043415,0.0121225,0.01357664,0.0001347298,0.001766025,0.1678843,0.001417056,0.003612358,0.01746831,0.1376078,0.643417],"study_design_scores_gemma":[0.0001114629,0.0005223668,0.03561834,0.0136634,0.0002805931,0.0002757781,0.1574245,0.00159265,0.003191292,0.002174282,0.7849212,0.000224041],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.491798,0.08276856,0.005688717,0.09010981,0.002558148,0.005254023,0.003527822,0.0006435476,0.3176513],"genre_scores_gemma":[0.7693902,0.1261685,0.01629102,0.008682313,0.0002009017,0.001895624,0.001404871,0.0002516505,0.075715],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1441833,"threshold_uncertainty_score":0.2900649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02110315973271511,"score_gpt":0.3200072753333192,"score_spread":0.2989041156006041,"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."}}