{"id":"W4392456009","doi":"10.1061/9780784485231.028","title":"SPEAR: Social Presence Enabled Augmented Reality Tool for Engineering Education","year":2024,"lang":"en","type":"article","venue":"","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fluidigm (Canada)","funders":"","keywords":"Augmented reality; Spear; Computer science; Human–computer interaction; 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":[0.0005519728,0.0009343129,0.0003987935,0.0008235261,0.0003390864,0.001340959,0.00143391,0.001132391,0.01483906],"category_scores_gemma":[0.001560999,0.000417706,0.0008041361,0.0002920269,0.000302079,0.00142106,0.002456211,0.0009068033,0.004376745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001359839,"about_ca_system_score_gemma":0.0003188331,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002839971,"about_ca_topic_score_gemma":0.0005569734,"domain_scores_codex":[0.999143,0.0001628955,0.00004868095,0.0001017366,0.0004505824,0.00009300129],"domain_scores_gemma":[0.9993784,0.0002754931,0.00005864327,0.0001036746,0.0001067628,0.00007698403],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006550917,0.0009190197,0.002677298,0.00186048,0.0001416885,0.002020119,0.002325825,0.004816851,0.1196776,0.01156505,0.04421574,0.8091252],"study_design_scores_gemma":[0.0003099423,0.002241428,0.0135025,0.0007669727,0.000286594,0.009131286,0.001077593,0.07152059,0.1252546,0.01085101,0.7645143,0.0005432249],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07549006,0.002174013,0.8237531,0.0007457486,0.0006180899,0.001092026,0.001210923,0.04478253,0.05013361],"genre_scores_gemma":[0.4511549,0.00222494,0.4933254,0.0007834023,0.0002821183,0.001489018,0.001733046,0.002124225,0.04688302],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01483906,"threshold_uncertainty_score":0.04964155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02087010401738053,"score_gpt":0.2997913295415925,"score_spread":0.2789212255242119,"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."}}