{"id":"W2088540292","doi":"10.1109/vast.2014.7042529","title":"The care and condition monitor: Designing a tablet based tool for visualizing informal qualitative healthcare data","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario College of Art and Design","funders":"Mitacs","keywords":"Visualization; Scope (computer science); Health care; Data visualization; Structuring; Computer science; Comprehension; Visual analytics; Analytics; Qualitative research; Human–computer interaction; Data science; Knowledge management; Multimedia; Data mining","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001022102,0.0000885463,0.00009689199,0.00004476704,0.0005146554,0.0005199694,0.0005934645,0.00003213119,0.000001668213],"category_scores_gemma":[0.0003279241,0.00006384089,0.00001634765,0.0001481403,0.00004257865,0.001002531,0.0002358179,0.00004766774,0.00000330067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001570537,"about_ca_system_score_gemma":0.00007535759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003842136,"about_ca_topic_score_gemma":0.00003491741,"domain_scores_codex":[0.999005,0.0001632198,0.0002189232,0.0002344743,0.0001807411,0.0001976043],"domain_scores_gemma":[0.998372,0.0007604112,0.00009979808,0.0005145644,0.0001925793,0.00006069484],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001900467,0.00001912957,0.0004316636,0.0002592177,0.00002518194,4.598386e-7,0.01353496,0.00011415,0.0001086328,0.8758497,0.0090583,0.1005796],"study_design_scores_gemma":[0.0005096928,0.0001647313,0.00006871088,0.0000385609,0.000007676505,0.000001139534,0.006836957,0.9544333,0.0007239688,0.0007970686,0.03626306,0.0001551669],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0004719283,0.00007662923,0.9980525,0.0006904024,0.00009068755,0.0002048719,0.0001041164,0.0000823813,0.0002265221],"genre_scores_gemma":[0.8412873,0.00002288999,0.1547557,0.002685657,0.000085432,0.00003176555,0.001021121,0.00001115275,0.00009899165],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9543191,"threshold_uncertainty_score":0.5014077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07471421459530998,"score_gpt":0.4162442121426042,"score_spread":0.3415299975472942,"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."}}