{"id":"W2885997568","doi":"10.1016/j.promfg.2018.07.140","title":"Design and Interaction Interface using Augmented Reality for Smart Manufacturing","year":2018,"lang":"en","type":"article","venue":"Procedia Manufacturing","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Interface (matter); Computer science; Augmented reality; Human–computer interaction; Virtual machine; Personalization; Sketch; Object (grammar); Virtual prototyping; Set (abstract data type); User interface; Virtual finite-state machine; Embedded system; Simulation; Artificial intelligence; Operating system","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005167383,0.0002482959,0.0002069748,0.0001621457,0.0004542503,0.0002774898,0.0005248139,0.00009474747,0.000009947041],"category_scores_gemma":[0.00004605109,0.0002487945,0.00005048982,0.00009489978,0.00009928316,0.0009369476,0.0004051125,0.0001813148,0.00001780258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002056583,"about_ca_system_score_gemma":0.00004825927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008099476,"about_ca_topic_score_gemma":0.00001389385,"domain_scores_codex":[0.9982414,0.0000592529,0.0003623423,0.0006999433,0.0001992304,0.0004377898],"domain_scores_gemma":[0.9988302,0.0002143039,0.0002222477,0.0005037824,0.00008526706,0.0001441707],"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":[0.0009484597,0.0008594821,0.0002747357,0.002129654,0.0008962227,0.00001582798,0.01771961,0.03386523,0.2525059,0.009559719,0.00483788,0.6763873],"study_design_scores_gemma":[0.0003047651,0.00007169706,0.0003423925,0.00005467226,0.00002013139,0.00003936835,0.00006028679,0.2683638,0.7243315,0.004039757,0.00215225,0.0002193853],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1137148,0.00002652881,0.8839048,0.0006251838,0.0003183069,0.000896723,0.000003486953,0.0003089735,0.0002012038],"genre_scores_gemma":[0.8491321,0.00001139955,0.1503148,0.000128728,0.0001744346,0.0001294471,0.000004751958,0.0000245239,0.0000799125],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7354172,"threshold_uncertainty_score":0.9999964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06964403189139992,"score_gpt":0.3264905095059359,"score_spread":0.2568464776145361,"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."}}