{"id":"W4252441607","doi":"10.1145/765978.765981","title":"EyePliances","year":2003,"lang":"en","type":"article","venue":"CHI '03 extended abstracts on Human factors in computer systems - CHI '03","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science","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":[0.0006074492,0.001498298,0.0005298273,0.001093233,0.0007229239,0.002042179,0.002070852,0.001795976,0.08948272],"category_scores_gemma":[0.002407194,0.0005398894,0.0006811474,0.0007015978,0.0003604964,0.003716834,0.002975357,0.001127655,0.03885489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004090364,"about_ca_system_score_gemma":0.0005550581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001339964,"about_ca_topic_score_gemma":0.001984346,"domain_scores_codex":[0.9993359,0.00007084054,0.00003899105,0.0001746715,0.0002819685,0.00009754333],"domain_scores_gemma":[0.999212,0.0001503879,0.00004904174,0.0002342408,0.0002456862,0.0001085105],"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":[0.001345097,0.0002232008,0.002313862,0.0009703026,0.00008355916,0.0008970068,0.0004477732,0.001256568,0.04768728,0.01655928,0.2693622,0.6588539],"study_design_scores_gemma":[0.0001732745,0.0003841871,0.001864256,0.0001563569,0.00008677992,0.002251678,0.0001031013,0.007979098,0.03746334,0.006976299,0.9424492,0.0001124846],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02829,0.01048605,0.4998139,0.002655154,0.002154355,0.001035307,0.01111959,0.1448018,0.2996439],"genre_scores_gemma":[0.2200063,0.007881543,0.280462,0.005423454,0.0008874136,0.00144852,0.02554577,0.0156663,0.4426788],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08948272,"threshold_uncertainty_score":0.2993495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04840372363746705,"score_gpt":0.2955110176671237,"score_spread":0.2471072940296566,"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."}}