{"id":"W2129659699","doi":"10.1145/2254556.2254694","title":"Seamless mixed reality tracking in tabletop reservoir engineering interaction","year":2012,"lang":"en","type":"article","venue":"","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Workspace; Computer science; Mixed reality; Context (archaeology); Human–computer interaction; Tracking (education); Augmented reality; Mobile device; Interface (matter); World Wide Web; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008694639,0.0007171459,0.0006371287,0.0004775062,0.0005238758,0.002301841,0.001450098,0.001653728,0.004949392],"category_scores_gemma":[0.004007982,0.0007587312,0.0006266963,0.0004489909,0.0006884453,0.002341971,0.003769802,0.0007897835,0.001301466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002959066,"about_ca_system_score_gemma":0.0003778462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001047794,"about_ca_topic_score_gemma":0.001108321,"domain_scores_codex":[0.9983349,0.0004844186,0.00007499348,0.0003079631,0.0006736299,0.0001240808],"domain_scores_gemma":[0.9983633,0.0008382898,0.0001284269,0.0004011411,0.0001660354,0.0001028443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001619846,0.0003485815,0.003015705,0.0005495527,0.000190396,0.002459385,0.004554032,0.06271578,0.420666,0.01753641,0.005825598,0.4805187],"study_design_scores_gemma":[0.000240159,0.001105711,0.005824971,0.0001906002,0.0001640036,0.003738106,0.0009057216,0.6697459,0.2363142,0.01033793,0.07100334,0.0004293287],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04005219,0.0002681055,0.9540401,0.0001180148,0.000061084,0.00008269569,0.00004714568,0.001863634,0.003466987],"genre_scores_gemma":[0.5289658,0.0003306137,0.4624693,0.0001966275,0.00004876534,0.0001956647,0.0001483281,0.0003505042,0.007294359],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004949392,"threshold_uncertainty_score":0.01655734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05210878319036819,"score_gpt":0.3137173184274732,"score_spread":0.261608535237105,"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."}}