{"id":"W4387810005","doi":"10.2196/45828","title":"Connect Brain, a Mobile App for Studying Depth Perception in Angiography Visualization: Gamification Study","year":2023,"lang":"en","type":"article","venue":"JMIR Neurotechnology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visualization; Computer science; Human–computer interaction; Rendering (computer graphics); Perception; Context (archaeology); Creative visualization; Mobile device; Multimedia; Android (operating system); Volume rendering; Data science; World Wide Web; Artificial intelligence; Psychology","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":[0.0003803292,0.0001409152,0.0001879583,0.001286517,0.0001348286,0.000101171,0.0006796333,0.0001172885,0.000005290844],"category_scores_gemma":[0.0001216788,0.0001510302,0.00008077431,0.004084013,0.0000458169,0.0002905741,0.0002300798,0.0001121606,0.0000533399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002595883,"about_ca_system_score_gemma":0.00002251237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005951663,"about_ca_topic_score_gemma":0.00004173884,"domain_scores_codex":[0.9985068,0.0001198448,0.0003351507,0.0005749469,0.0001803765,0.000282859],"domain_scores_gemma":[0.9990309,0.0001268235,0.0001149645,0.0005997303,0.00009349045,0.00003411689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001225363,0.006987919,0.1934707,0.0003760255,0.0002482168,0.0001959017,0.02282277,0.006821784,0.03954159,0.3394202,0.04009775,0.3498946],"study_design_scores_gemma":[0.003325113,0.002577351,0.1737805,0.00003522945,0.00002562123,0.00001873327,0.007055689,0.783523,0.0004534159,0.003940199,0.02454781,0.000717413],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4476583,0.00001792244,0.5459985,0.001384291,0.0001878522,0.002815264,0.000007667465,0.001896159,0.00003400649],"genre_scores_gemma":[0.997447,0.00001711249,0.0005609168,0.0004257311,0.00002497463,0.001364516,0.00006808294,0.00002068932,0.00007102136],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7767012,"threshold_uncertainty_score":0.6158832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04212967323006492,"score_gpt":0.3600946178990866,"score_spread":0.3179649446690216,"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."}}