{"id":"W1526642635","doi":"10.11575/prism/33287","title":"Increasing the dimensionality of a Geographic Information System (GIS) Using Auditory Display","year":2007,"lang":"en","type":"article","venue":"Open MIND","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Sonification; Computer science; Raster graphics; Variety (cybernetics); Sight; Human–computer interaction; Auditory display; Sound (geography); Spatial analysis; Geographic information system; Perception; Computer vision; Artificial intelligence; Geography; Cartography; Remote sensing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004268579,0.00006570368,0.00009597336,0.00007686571,0.0002765922,0.00009531874,0.0002291143,0.00003520897,0.00008926564],"category_scores_gemma":[0.0002614686,0.00004615101,0.00004495284,0.0001918522,0.0000788609,0.000852479,0.00009683951,0.0001124867,0.00007562132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004149814,"about_ca_system_score_gemma":0.00003726863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004828066,"about_ca_topic_score_gemma":0.00003987296,"domain_scores_codex":[0.9991455,0.0001218447,0.0002862277,0.0001098065,0.0002072903,0.0001293392],"domain_scores_gemma":[0.9990359,0.0004285646,0.0002256452,0.000220396,0.00005170705,0.00003778279],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003052917,0.00007990821,0.009725556,0.00002672605,0.0000168159,0.00001158269,0.00209523,0.0003515424,0.9768911,0.0009432256,0.00004135713,0.009511667],"study_design_scores_gemma":[0.0007475114,0.0000719025,0.07863377,0.0003547979,0.00009522789,0.0007385592,0.006648722,0.01252164,0.8394606,0.00003344368,0.06033879,0.0003550343],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9868234,0.000001130941,0.0003067502,0.00003007131,0.0004785025,0.0002248917,0.00001898352,0.00000225677,0.01211403],"genre_scores_gemma":[0.999552,5.615843e-7,0.0002879957,0.00006472796,0.00005279174,0.000001514154,0.000001770151,0.000003211959,0.00003540235],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1374305,"threshold_uncertainty_score":0.2127351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05929537180880094,"score_gpt":0.326834884752479,"score_spread":0.267539512943678,"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."}}