{"id":"W4396217314","doi":"10.21203/rs.3.rs-3909704/v2","title":"E2GO : Free Your Hands for Smartphone Interaction","year":2024,"lang":"en","type":"preprint","venue":"Research Square","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Gaze; Computer science; Fixation (population genetics); Eye tracking; Human–computer interaction; Event (particle physics); Jitter; Power consumption; Cover (algebra); Artificial intelligence; Power (physics); 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":[0.000713994,0.001944927,0.001065765,0.0009596336,0.0005653204,0.001682484,0.001729264,0.001974863,0.1356336],"category_scores_gemma":[0.003181316,0.0007983582,0.0007262646,0.0004519564,0.0003800485,0.002203802,0.00476973,0.001362552,0.04367987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002588125,"about_ca_system_score_gemma":0.0003463848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00125152,"about_ca_topic_score_gemma":0.00240057,"domain_scores_codex":[0.9992201,0.00009848276,0.00004495246,0.0001377893,0.0003384252,0.0001603078],"domain_scores_gemma":[0.9986998,0.0003550165,0.00004818584,0.000481578,0.0001995959,0.0002157286],"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":[0.004378091,0.0005296111,0.001738547,0.001049424,0.0002060032,0.0009985275,0.0008977064,0.001458621,0.1045074,0.009106391,0.3759159,0.4992138],"study_design_scores_gemma":[0.001918887,0.001243723,0.01304716,0.0005282018,0.0002868013,0.002923383,0.0003664816,0.06801956,0.1726633,0.02317694,0.715255,0.0005706091],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.03118811,0.001586859,0.4452059,0.000786573,0.0009377822,0.0009697122,0.01183621,0.4540978,0.05339102],"genre_scores_gemma":[0.369563,0.001429935,0.1982671,0.00195805,0.0005071486,0.00222464,0.02740283,0.07279572,0.3258516],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1356336,"threshold_uncertainty_score":0.4537397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1388876273546214,"score_gpt":0.4443581471064039,"score_spread":0.3054705197517825,"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."}}