{"id":"W2942028982","doi":"10.1145/3290605.3300870","title":"Peripheral Notifications in Large Displays","year":2019,"lang":"en","type":"article","venue":"","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Notice; Feature (linguistics); Visual field; Peripheral vision; Human–computer interaction; Artificial intelligence; Peripheral; Computer vision; Neuroscience; 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":[0.00267179,0.0004725723,0.0004473384,0.0004706972,0.0006635145,0.00193078,0.0007535736,0.0007285164,0.007413895],"category_scores_gemma":[0.03553774,0.0004219816,0.0002725958,0.0004289269,0.0006211607,0.002319231,0.001636481,0.0006299672,0.0008406818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004755457,"about_ca_system_score_gemma":0.0003931014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009556686,"about_ca_topic_score_gemma":0.0007180499,"domain_scores_codex":[0.9975666,0.001274234,0.0001281101,0.0002921115,0.0005912451,0.0001476993],"domain_scores_gemma":[0.9702039,0.02267073,0.002750634,0.002108006,0.001332787,0.0009338472],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.01129387,0.001292835,0.05109022,0.002576778,0.000125172,0.001937099,0.01657598,0.01263889,0.3408174,0.0248796,0.007607104,0.5291652],"study_design_scores_gemma":[0.001415671,0.01671352,0.4476747,0.001392992,0.0008012379,0.006363534,0.007432042,0.1344186,0.2137559,0.07773218,0.09163138,0.0006683054],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8654016,0.001445438,0.1070055,0.0003936634,0.0001310346,0.0002274025,0.0001252409,0.002105882,0.02316419],"genre_scores_gemma":[0.9782326,0.0001860336,0.01944212,0.00008859534,0.00004639548,0.00006255566,0.00005417687,0.00009340005,0.001794077],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007413895,"threshold_uncertainty_score":0.02480197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.198516319461116,"score_gpt":0.4389554319069862,"score_spread":0.2404391124458702,"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."}}