{"id":"W4409885299","doi":"10.1145/3706598.3713781","title":"There Is More to Dwell Than Meets the Eye: Toward Better Gaze-Based Text Entry Systems With Multi-Threshold Dwell","year":2025,"lang":"en","type":"article","venue":"","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; Simon Fraser University","funders":"","keywords":"Dwell time; Computer science; Gaze; Eye tracking; Artificial intelligence; Computer vision; Psychology","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":[0.001140183,0.0006601517,0.0004721629,0.0006774428,0.0002773688,0.001031233,0.001137873,0.0007999155,0.01177976],"category_scores_gemma":[0.004343805,0.0003715184,0.0002694578,0.0004230973,0.0002802898,0.002441772,0.001120652,0.0005323881,0.001730981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004999583,"about_ca_system_score_gemma":0.0005043713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002022118,"about_ca_topic_score_gemma":0.002334184,"domain_scores_codex":[0.9992889,0.0001570218,0.0000694241,0.0002194086,0.0002096147,0.00005545904],"domain_scores_gemma":[0.9971572,0.00105984,0.0002025265,0.0003776058,0.0009804227,0.0002223686],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004213221,0.0005088346,0.004248326,0.0008941451,0.00007940475,0.000147457,0.0005904874,0.00231407,0.660821,0.001658115,0.003163412,0.3213616],"study_design_scores_gemma":[0.001489772,0.01470932,0.05528017,0.0004740172,0.0006086447,0.004113436,0.0008183085,0.1757827,0.7023761,0.003329939,0.04053336,0.0004842232],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6627771,0.003833745,0.321082,0.0008161428,0.0003241031,0.0004722855,0.0005819819,0.006495057,0.00361776],"genre_scores_gemma":[0.7591597,0.0009278909,0.2331664,0.0003191798,0.00008855555,0.0001615818,0.0002743436,0.0003382472,0.005564161],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01177976,"threshold_uncertainty_score":0.03940719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01663622418376365,"score_gpt":0.2602796677106073,"score_spread":0.2436434435268437,"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."}}