{"id":"W2896098622","doi":"10.1145/3267782.3267798","title":"Look to Go","year":2018,"lang":"en","type":"article","venue":"","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Nvidia","keywords":"Computer vision; Optical head-mounted display; Computer science; Artificial intelligence; Eye tracking; Virtual reality; Head (geology); Terrain; Tracking (education); Eye movement; Simulation; Computer graphics (images); Geography; Psychology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00005710104,0.00003644582,0.00004023143,0.00005182686,0.00004062582,0.00002915169,0.0004805339,0.00002216415,0.00005397088],"category_scores_gemma":[0.00001831523,0.00002898505,0.00001110745,0.0002038722,0.00003675757,0.00005390244,0.000158364,0.00003035221,0.005504752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007629145,"about_ca_system_score_gemma":0.000009837197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006426805,"about_ca_topic_score_gemma":0.0000149021,"domain_scores_codex":[0.999607,0.000005536408,0.00004485487,0.0001627128,0.0000523601,0.0001275398],"domain_scores_gemma":[0.9995985,0.00001060358,0.000007670744,0.0003047338,0.00004104653,0.00003743007],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[8.96481e-7,0.00002520483,0.001860921,7.401431e-7,0.000003764872,0.00000535305,0.0001110547,4.566323e-7,0.003289316,0.7106559,0.08915067,0.1948958],"study_design_scores_gemma":[0.0002675082,0.0007802996,0.06798761,0.00001415051,0.000002432419,0.00003220524,0.00002300875,0.004577699,0.1531897,0.03659527,0.7361469,0.0003831222],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0237639,0.000002708829,0.8759976,0.004567351,0.0002023525,0.00002666819,9.059387e-8,0.0005293391,0.09491001],"genre_scores_gemma":[0.873755,1.234539e-7,0.1191335,0.001394597,0.0000497215,0.000002205286,3.706905e-8,0.000001636452,0.005663097],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8499911,"threshold_uncertainty_score":0.9952696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01581794608227024,"score_gpt":0.2617414138936957,"score_spread":0.2459234678114254,"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."}}