{"id":"W3048699628","doi":"10.11575/prism/38068","title":"Health Visualizations at Home: Who Sees What Where","year":2018,"lang":"en","type":"article","venue":"Open MIND","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; Alberta Innovates - Technology Futures","keywords":"Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02385566,0.0004547763,0.0006045256,0.0008681932,0.004080335,0.004090482,0.001375458,0.002320982,0.004878815],"category_scores_gemma":[0.04616442,0.0006100828,0.0004460246,0.0006218416,0.005311694,0.007143422,0.004348148,0.002182237,0.0005238211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002647237,"about_ca_system_score_gemma":0.002380464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005383771,"about_ca_topic_score_gemma":0.004903458,"domain_scores_codex":[0.9829979,0.0137896,0.0004609389,0.0007870622,0.0009399051,0.001024581],"domain_scores_gemma":[0.9548385,0.03540449,0.001742439,0.001609413,0.00381365,0.00259165],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001129128,0.00009150535,0.008181104,0.0004611442,0.00001029591,0.000857753,0.9713293,0.0001852666,0.002815792,0.004162826,0.001610175,0.01018187],"study_design_scores_gemma":[0.00003516712,0.0002594937,0.006098434,0.0006189251,0.00002596376,0.0004558202,0.9499453,0.001036032,0.001833582,0.003398363,0.03621338,0.00007953895],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9273584,0.0006347215,0.04330216,0.01239244,0.0001460241,0.000592051,0.0003856873,0.000328584,0.01485986],"genre_scores_gemma":[0.9890342,0.0002109241,0.008593761,0.0006275541,0.0000165446,0.0002271855,0.00004301286,0.00005545724,0.001191455],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02385566,"threshold_uncertainty_score":0.1261623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05274606944192348,"score_gpt":0.3894156355820954,"score_spread":0.3366695661401719,"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."}}