{"id":"W4414015845","doi":"10.11159/icbes25.203","title":"Spatial Language in Augmented Reality: An XR Framework for Investigating Visuospatial Cognition","year":2025,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Augmented reality; Cognition; Computer science; Spatial cognition; Human–computer interaction; Cognitive psychology; Virtual reality; Mixed reality; Psychology; Neuroscience","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0007751424,0.001296412,0.0005923107,0.002017418,0.0005659334,0.003789597,0.00165071,0.0014706,0.004547666],"category_scores_gemma":[0.001598381,0.0003691569,0.001001271,0.001455692,0.003416626,0.002662405,0.003271684,0.001147222,0.000816614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006669959,"about_ca_system_score_gemma":0.0006324584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001547452,"about_ca_topic_score_gemma":0.001674831,"domain_scores_codex":[0.9992515,0.0003288251,0.00003822776,0.0002112059,0.0001147574,0.00005546215],"domain_scores_gemma":[0.9993795,0.0002644363,0.0001068716,0.00011338,0.00007060917,0.00006508483],"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":[0.0004467498,0.0003721332,0.004877149,0.002325041,0.0003405357,0.001521272,0.006189791,0.02912267,0.0614692,0.6796221,0.003323126,0.2103903],"study_design_scores_gemma":[0.0001681847,0.001944097,0.02098284,0.001145706,0.0004469288,0.002724668,0.006071188,0.1517263,0.01270984,0.6908809,0.1108305,0.0003689143],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03928154,0.01688035,0.8983878,0.001621169,0.0002669565,0.0003135415,0.0006746845,0.0003503744,0.04222363],"genre_scores_gemma":[0.4749158,0.008750973,0.508809,0.0004356897,0.000445036,0.001183806,0.0004697439,0.00007876522,0.004911068],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004547666,"threshold_uncertainty_score":0.01521343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01130418092636322,"score_gpt":0.2644377998527658,"score_spread":0.2531336189264026,"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."}}