{"id":"W2762293468","doi":"10.1145/3131277.3134367","title":"Artificial landmarks augmented linear control widgets to improve spatial learning and revisitation performance","year":2017,"lang":"en","type":"article","venue":"","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Thumbnail; Computer science; Task (project management); Control (management); Artificial intelligence; Human–computer interaction; Computer vision; Image (mathematics); Engineering","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":[0.000306717,0.0007298156,0.0004375802,0.000397468,0.0001471127,0.0008232621,0.001019922,0.0005667347,0.005968736],"category_scores_gemma":[0.00361128,0.0002317965,0.0002946614,0.0002738642,0.0002647311,0.001069724,0.0008337581,0.0004061197,0.0009054293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001809309,"about_ca_system_score_gemma":0.0003103737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001397644,"about_ca_topic_score_gemma":0.001519962,"domain_scores_codex":[0.999683,0.00005403098,0.00002768262,0.00007703703,0.0001117912,0.00004644158],"domain_scores_gemma":[0.9983088,0.0007865703,0.0001618659,0.0003323189,0.0003062686,0.0001041435],"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":[0.001980802,0.0006577005,0.002566156,0.0007663613,0.00007093509,0.0003831334,0.0005990742,0.0302142,0.415532,0.002336183,0.002777359,0.5421161],"study_design_scores_gemma":[0.000221764,0.00524725,0.01137065,0.0001332412,0.0002687214,0.0007944091,0.0004763276,0.4004997,0.5482605,0.001831161,0.03066206,0.0002343014],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5830712,0.001099281,0.3970821,0.0001206969,0.0002458748,0.0001854141,0.0002376528,0.01150196,0.006455803],"genre_scores_gemma":[0.8351964,0.0002382245,0.1584434,0.00006627317,0.00001821426,0.0001085187,0.0002620945,0.0003507925,0.005316121],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005968736,"threshold_uncertainty_score":0.01996744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01170843366080666,"score_gpt":0.2779543872181595,"score_spread":0.2662459535573529,"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."}}