{"id":"W2983459912","doi":"10.1016/j.autcon.2019.102935","title":"Impact of augmented reality and spatial cognition on assembly in construction","year":2019,"lang":"en","type":"article","venue":"Automation in Construction","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":109,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Augmented reality; Rework; Workflow; Cognition; Interface (matter); Virtual reality; Human–computer interaction; Relation (database); Engineering; Computer science; Simulation; Psychology; Data mining","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":[0.001094292,0.0007675451,0.0003103986,0.001243709,0.0007598045,0.005695437,0.0007008043,0.001002066,0.01142137],"category_scores_gemma":[0.01061181,0.0004209518,0.0007934973,0.0007745576,0.003109944,0.002996344,0.003081186,0.0006978123,0.0004763268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001047818,"about_ca_system_score_gemma":0.0009751767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009659933,"about_ca_topic_score_gemma":0.007191932,"domain_scores_codex":[0.9981846,0.0007218739,0.00009268129,0.0002663135,0.0005351104,0.0001993518],"domain_scores_gemma":[0.9938645,0.003984525,0.0006992122,0.0006208128,0.0006366268,0.0001943629],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.007418484,0.001643395,0.1030246,0.001956973,0.0007183183,0.00290595,0.06551561,0.08887204,0.0774499,0.1846271,0.002740584,0.463127],"study_design_scores_gemma":[0.0004007906,0.003803352,0.5839924,0.0008532303,0.001377718,0.00302953,0.06911822,0.1275192,0.03763159,0.1354348,0.03626638,0.0005728446],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8945957,0.001029925,0.02611069,0.0005137668,0.00008051233,0.00002950831,0.0001098898,0.0001786907,0.07735127],"genre_scores_gemma":[0.9960793,0.0001582381,0.002397121,0.00001419404,0.00000856394,0.000005883385,0.0000203023,0.00001646839,0.001300033],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01142137,"threshold_uncertainty_score":0.03820831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01378396899725937,"score_gpt":0.2909344857918744,"score_spread":0.277150516794615,"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."}}