{"id":"W2081319021","doi":"10.1145/1268517.1268552","title":"Understanding the design space of referencing in collaborative augmented reality environments","year":2007,"lang":"en","type":"article","venue":"Proceedings","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Human–computer interaction; Augmented reality; Computer science; Workspace; Set (abstract data type); Context (archaeology); Space (punctuation); Task (project management); Virtual reality; Gaze; Mixed reality; Multimedia; Artificial intelligence; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001796232,0.0001062998,0.0001300381,0.0001112266,0.0001334154,0.0000457997,0.000557075,0.00005555271,0.000002814269],"category_scores_gemma":[0.00008482132,0.000084296,0.00002028364,0.001095479,0.0001047651,0.0003057379,0.0001749649,0.0001554924,0.000004281185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000479599,"about_ca_system_score_gemma":0.0000561404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004786453,"about_ca_topic_score_gemma":0.00002755117,"domain_scores_codex":[0.9988092,0.00002520339,0.0003052849,0.0002810293,0.0003226758,0.0002565884],"domain_scores_gemma":[0.9992952,0.0001728689,0.0002364867,0.0001936408,0.00004887235,0.00005293661],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005851451,0.0002155733,0.00274043,0.00004288301,0.00004811086,0.000003258787,0.0198013,0.0007969709,0.06761964,0.9053752,0.00149123,0.001806934],"study_design_scores_gemma":[0.003042089,0.0004751007,0.05126081,0.0004470837,0.00006926127,0.00003383904,0.04233539,0.1531043,0.5139736,0.2285103,0.005618346,0.001129859],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00629816,0.000022259,0.9837546,0.001757487,0.00002418261,0.0004809407,0.000001629891,0.00003896042,0.007621783],"genre_scores_gemma":[0.9892136,0.00002335484,0.01059388,0.00006122259,0.00001091998,0.00002630099,8.700999e-7,0.000006195994,0.00006368339],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9829154,"threshold_uncertainty_score":0.3437491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1180070456465841,"score_gpt":0.2936870186504399,"score_spread":0.1756799730038558,"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."}}