{"id":"W4412895137","doi":"10.1007/978-981-96-1154-6_12","title":"Toward Context Awareness in Mixed Reality: Supporting Spatial Reasoning with Object Detection and Ontologies","year":2025,"lang":"en","type":"book-chapter","venue":"Smart innovation, systems and technologies","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Caprion (Canada); Université de Sherbrooke","funders":"","keywords":"Spatial contextual awareness; Mixed reality; Computer science; Context (archaeology); Object (grammar); Spatial intelligence; Human–computer interaction; Augmented reality; Artificial intelligence; 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":[0.0009970611,0.0009504745,0.0007618298,0.00114013,0.0005545576,0.004829172,0.002340503,0.001260013,0.003779329],"category_scores_gemma":[0.002158082,0.0009232558,0.001248587,0.001464722,0.001311771,0.008985204,0.003432364,0.00261052,0.001677427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000591201,"about_ca_system_score_gemma":0.0007391713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003395597,"about_ca_topic_score_gemma":0.004703325,"domain_scores_codex":[0.9992002,0.0001554023,0.00005704416,0.0002179157,0.0003094112,0.00006000757],"domain_scores_gemma":[0.9993128,0.0003209857,0.0000405087,0.0001632804,0.0001173691,0.0000451455],"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":[0.0001263069,0.0001375092,0.0006642326,0.0006929094,0.0001431625,0.000325664,0.001726773,0.02486536,0.01589593,0.4510243,0.01383446,0.4905633],"study_design_scores_gemma":[0.00001845461,0.0000607181,0.0005903973,0.0002593634,0.0001601907,0.0005294859,0.0006162268,0.3098733,0.02036681,0.5255015,0.1419559,0.00006757921],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003349596,0.00205315,0.9827995,0.0003375862,0.0001083656,0.00002169003,0.0001074815,0.001079909,0.01014266],"genre_scores_gemma":[0.1236136,0.003447125,0.8625365,0.0002769136,0.0000883235,0.00005798067,0.0005897599,0.0003297707,0.009060029],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004829172,"threshold_uncertainty_score":0.0126431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02283419479158503,"score_gpt":0.2279358595244657,"score_spread":0.2051016647328807,"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."}}