{"id":"W3031080888","doi":"10.1145/3396339.3396390","title":"Tracing shapes with eyes","year":2020,"lang":"en","type":"article","venue":"","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Sketch; Gaze; Computer science; Tracing; Pointer (user interface); Computer vision; TRACE (psycholinguistics); Artificial intelligence; Eye tracking; Set (abstract data type); Human–computer interaction; Interface (matter); Computer graphics (images); Algorithm","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":[0.0005121815,0.0008769589,0.0004822897,0.0008779935,0.0004702335,0.001546167,0.001100905,0.001164313,0.0173347],"category_scores_gemma":[0.008335597,0.0005170997,0.0005719032,0.0005194455,0.0006468524,0.002781864,0.003393435,0.0006925952,0.003610143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00044039,"about_ca_system_score_gemma":0.0004601219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002039623,"about_ca_topic_score_gemma":0.002009079,"domain_scores_codex":[0.9992728,0.0001349222,0.00004648822,0.0002168371,0.000275009,0.00005396628],"domain_scores_gemma":[0.9970331,0.00126276,0.0002108494,0.0009235239,0.000451591,0.0001181876],"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":[0.0007031203,0.0001085277,0.00747731,0.0007188801,0.00008571073,0.0005232319,0.004912965,0.005884625,0.2432931,0.006383991,0.006746776,0.7231618],"study_design_scores_gemma":[0.0004375168,0.002537372,0.06466176,0.001031619,0.0003123576,0.005250299,0.005502393,0.1600967,0.5094845,0.04144239,0.2085842,0.0006588061],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2879176,0.001171095,0.6723737,0.0004568727,0.0002117767,0.0003980471,0.001010009,0.00923914,0.02722177],"genre_scores_gemma":[0.6435663,0.0009184931,0.3401947,0.0002974231,0.00004178613,0.0003123248,0.00063511,0.0008275733,0.01320634],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0173347,"threshold_uncertainty_score":0.05799037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02096097494346696,"score_gpt":0.2189398766772461,"score_spread":0.1979789017337792,"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."}}