{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000506561,0.00004486818,0.00005328512,0.00002225429,0.000387905,0.0001497577,0.0001284349,0.00003038854,0.0008462871],"category_scores_gemma":[0.0005279365,0.00004057193,0.00004754889,0.00009202258,0.000449351,0.0005793566,0.0000260412,0.0000135533,0.0001206795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007854339,"about_ca_system_score_gemma":0.0001358371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002564352,"about_ca_topic_score_gemma":0.0011755,"domain_scores_codex":[0.9992975,0.00002538122,0.0001097592,0.0001365588,0.0002252306,0.0002055422],"domain_scores_gemma":[0.9994951,0.0002057829,0.00002437895,0.00005260715,0.0001601646,0.00006189026],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00016303,0.0008684556,0.1389712,0.0000466251,0.00007069667,4.402861e-7,0.04770915,0.000002202819,0.0009497084,0.7129022,0.02613587,0.07218038],"study_design_scores_gemma":[0.000933983,0.0009684919,0.01900121,0.00002420659,0.00002111901,5.049346e-7,0.05880784,0.0005170121,0.006577003,0.8425372,0.07008535,0.000526097],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6312376,0.000003069282,0.01150009,0.000514282,0.0002265476,0.0003728333,0.000006495709,0.0001236052,0.3560154],"genre_scores_gemma":[0.9860661,1.961749e-7,0.004905892,0.0001902798,0.0003736387,0.00003176112,0.000005265534,0.000004473,0.008422397],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3548284,"threshold_uncertainty_score":0.9266251,"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."}}