{"id":"W7143604049","doi":"10.71465/ajainn634","title":"The Role of Deep Learning in Augmented Reality Applications","year":2024,"lang":"","type":"article","venue":"American Journal of Artificial Intelligence and Neural Networks","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Deep learning; Augmented reality; Object (grammar); Key (lock); Natural (archaeology); Visualization","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":[0.001654658,0.0002443357,0.0004700405,0.000237023,0.0004081303,0.0004009255,0.0009652194,0.00007997052,0.000009386874],"category_scores_gemma":[0.00007630559,0.0001887999,0.0002050138,0.002467403,0.001408183,0.000398033,0.0002387618,0.001269413,0.000003873518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000837857,"about_ca_system_score_gemma":0.0001218929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002380103,"about_ca_topic_score_gemma":0.0002245503,"domain_scores_codex":[0.9964723,0.0004879995,0.001731279,0.0004096693,0.0004169874,0.0004817605],"domain_scores_gemma":[0.9967524,0.001363601,0.0009943581,0.0004023371,0.000279072,0.000208279],"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":[0.00006337628,0.00008754844,0.0001667756,0.00001040983,0.00005998554,0.000008575907,0.0009738132,0.1475469,0.0001787796,0.03021693,0.000006957683,0.8206799],"study_design_scores_gemma":[0.00001755309,0.0005752704,0.0002279092,0.0001309393,0.00005500436,0.00008374613,0.004054479,0.976748,0.0007108978,0.01463073,0.002604933,0.0001604928],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01006706,0.01660842,0.9686611,0.003871354,0.0003063022,0.000345267,0.000002750612,0.00002544647,0.0001123026],"genre_scores_gemma":[0.9897091,0.009430826,0.0004076645,0.00006778334,0.0003297539,0.00002381569,0.000001481111,0.00001668841,0.00001289802],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.979642,"threshold_uncertainty_score":0.7699036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02273884781760641,"score_gpt":0.2998997447519079,"score_spread":0.2771608969343015,"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."}}