{"id":"W4412963424","doi":"10.1109/i2mtc62753.2025.11079049","title":"System for Drone-Based Indoor Mapping for Augmented Reality","year":2025,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"AGE-WELL","keywords":"Drone; Augmented reality; Computer science; Computer vision; Artificial intelligence; Computer graphics (images); Human–computer interaction","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003939421,0.0009595261,0.0007243134,0.001055103,0.0004455717,0.001055059,0.001267802,0.0009287153,0.02447651],"category_scores_gemma":[0.0006432312,0.000334341,0.0005169745,0.0005333386,0.0002241362,0.0007761954,0.001972293,0.0008890621,0.01216399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002581949,"about_ca_system_score_gemma":0.0006240255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001853604,"about_ca_topic_score_gemma":0.002487036,"domain_scores_codex":[0.999585,0.00006283067,0.00002142563,0.00009848725,0.0001855533,0.00004676291],"domain_scores_gemma":[0.9996578,0.00002955332,0.00002408056,0.0001358303,0.0001136064,0.00003924554],"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":[0.001031184,0.0003040235,0.003083049,0.0007677426,0.0001704828,0.0007773513,0.001043944,0.009588865,0.1695781,0.008306535,0.07031808,0.7350307],"study_design_scores_gemma":[0.0003845097,0.001165248,0.009960428,0.0002423442,0.0003095052,0.002924476,0.0007113614,0.3044031,0.1444551,0.005223834,0.5298981,0.0003219901],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02302688,0.0007033234,0.912457,0.0002908933,0.0005242161,0.0004565828,0.002702268,0.03551012,0.02432869],"genre_scores_gemma":[0.4512692,0.000697999,0.5070295,0.0005709294,0.000159468,0.0008722122,0.006162276,0.001044937,0.03219353],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02447651,"threshold_uncertainty_score":0.08188206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01970456487064744,"score_gpt":0.2423168044060307,"score_spread":0.2226122395353832,"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."}}