{"id":"W2896943372","doi":"10.1145/3242587.3242637","title":"Asterisk and Obelisk","year":2018,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Inertial measurement unit; Computer science; Motion (physics); Computer vision; Asterisk; Artificial intelligence; Orientation (vector space); Kinesthetic learning; Computer graphics (images); Mathematics; The Internet","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003139873,0.00003541808,0.00003287466,0.00002220972,0.00004986818,0.00005439455,0.000145272,0.00001074076,0.0001075873],"category_scores_gemma":[0.000007242959,0.0000273475,0.00001023259,0.00005013265,0.00003278781,0.00033438,0.0001189187,0.00002195332,0.0003609057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000034196,"about_ca_system_score_gemma":0.000005427422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000136035,"about_ca_topic_score_gemma":0.00000612017,"domain_scores_codex":[0.9997084,0.000008767202,0.00003753684,0.0001198554,0.00004147343,0.00008395214],"domain_scores_gemma":[0.9997662,0.0000126638,0.00001115465,0.0001263589,0.00005654017,0.00002706766],"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":[0.00002678298,0.00008428469,0.006616616,0.000008296691,0.00005262117,0.00001743146,0.005792808,1.352577e-7,0.270111,0.5548572,0.07784272,0.08459008],"study_design_scores_gemma":[0.0006636339,0.001027062,0.1947594,0.00002443531,0.00000778737,0.00009084449,0.0005498158,0.01931887,0.5534073,0.008198761,0.221456,0.000496067],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1335251,0.00002733402,0.6207015,0.0007314811,0.0004096833,0.00004144984,7.814735e-7,0.00002029982,0.2445423],"genre_scores_gemma":[0.9916168,0.000003198591,0.004920221,0.001556494,0.00005713955,8.611187e-7,1.461088e-7,0.000001411453,0.001843725],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8580917,"threshold_uncertainty_score":0.4638832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006821074078291699,"score_gpt":0.2396731891099753,"score_spread":0.2328521150316836,"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."}}