{"id":"W3025342261","doi":"10.1109/vrw50115.2020.00165","title":"Map Displays And Landmark Effects On Wayfinding In Unfamiliar Environments","year":2020,"lang":"en","type":"article","venue":"2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)","topic":"Spatial Cognition and Navigation","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Landmark; Computer science; Track (disk drive); Computer vision; Scale (ratio); Artificial intelligence; Virtual reality; Human–computer interaction; Computer graphics (images); Cartography; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006825175,0.0007520072,0.0004349697,0.0004624967,0.0003342894,0.001339826,0.0004528066,0.000720517,0.006982164],"category_scores_gemma":[0.01562174,0.0003366983,0.0003356089,0.0003290015,0.0004834913,0.002136257,0.001198621,0.0004616529,0.0005649453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000127919,"about_ca_system_score_gemma":0.000163554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006423297,"about_ca_topic_score_gemma":0.000722635,"domain_scores_codex":[0.9992033,0.0003604488,0.00005349501,0.0001294281,0.0001766653,0.00007678066],"domain_scores_gemma":[0.9850838,0.01181301,0.00119354,0.0008024441,0.0006884811,0.0004186866],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.01224622,0.001931506,0.05998271,0.003557544,0.0005466738,0.003353255,0.03477607,0.01039225,0.639783,0.002328204,0.002406808,0.2286958],"study_design_scores_gemma":[0.00113269,0.02866996,0.7195299,0.0006391985,0.001641067,0.002901781,0.02502817,0.01550716,0.1730311,0.006710767,0.02449458,0.000713638],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933961,0.0002720349,0.003514012,0.00003376753,0.00003946481,0.00002293283,0.00005311543,0.0001791637,0.002489481],"genre_scores_gemma":[0.9939585,0.0002868304,0.004304999,0.00002702435,0.00003386362,0.00005806682,0.00009187554,0.0001205011,0.001118314],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006982164,"threshold_uncertainty_score":0.02335769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02669056135754473,"score_gpt":0.2487285105676957,"score_spread":0.2220379492101509,"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."}}