{"id":"W2808031846","doi":"10.1145/3196709.3196760","title":"Designing for Situational Visual Impairments","year":2018,"lang":"en","type":"article","venue":"","topic":"Digital Accessibility for Disabilities","field":"Social Sciences","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Engineering and Physical Sciences Research Council","keywords":"Leverage (statistics); Situational ethics; Computer science; Key (lock); Mobile device; Human–computer interaction; World Wide Web; Computer security; Psychology; Artificial intelligence; Social 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":[0.0097484,0.0008292715,0.0003586082,0.001858446,0.002821346,0.003433121,0.001014804,0.001279793,0.004896095],"category_scores_gemma":[0.02651355,0.0004714738,0.0005951106,0.0005887591,0.003043774,0.003969167,0.005648785,0.001331177,0.001086356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001508342,"about_ca_system_score_gemma":0.003761218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001753015,"about_ca_topic_score_gemma":0.003259626,"domain_scores_codex":[0.9925194,0.00504253,0.0005245734,0.0004031614,0.0009263135,0.0005840378],"domain_scores_gemma":[0.9839762,0.009230034,0.00134031,0.002048546,0.002269834,0.001135116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001482555,0.0005915573,0.06470979,0.002995593,0.00009128897,0.002876019,0.5073826,0.002710605,0.01411132,0.03912965,0.01409842,0.3511549],"study_design_scores_gemma":[0.0001080164,0.0009088463,0.02773364,0.003150061,0.0003228607,0.006640228,0.3709199,0.005315867,0.01684948,0.04538026,0.5224816,0.0001891746],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7018835,0.001834986,0.1924127,0.006879409,0.000238611,0.0009828164,0.0001918929,0.001721902,0.0938542],"genre_scores_gemma":[0.8969035,0.001128188,0.0931158,0.0009008865,0.0000259045,0.0005643386,0.00009458111,0.000169809,0.007097062],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0097484,"threshold_uncertainty_score":0.0515551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.045293060983877,"score_gpt":0.4042679593288752,"score_spread":0.3589748983449982,"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."}}