{"id":"W2029923333","doi":"10.1145/2470654.2481295","title":"SeeSay and HearSay CAPTCHA for mobile interaction","year":2013,"lang":"en","type":"article","venue":"","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"CAPTCHA; Hearsay; Computer science; Human–computer interaction; Modality (human–computer interaction); Text entry; Mobile device; Usability; World Wide Web","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":[0.000085145,0.00004148482,0.00005406633,0.00003410575,0.00004346976,0.0001752836,0.0001234911,0.00002035868,0.00005836571],"category_scores_gemma":[0.000007194052,0.0000334799,0.0000185187,0.00004834849,0.000008315796,0.0004207986,0.00003884397,0.00002350686,0.0001649478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008316033,"about_ca_system_score_gemma":0.000006496991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001409694,"about_ca_topic_score_gemma":0.00001744711,"domain_scores_codex":[0.9996098,0.00001529023,0.00009449504,0.0001412042,0.00005465899,0.00008454183],"domain_scores_gemma":[0.9996569,0.00004767327,0.00002274587,0.0001683286,0.00005547756,0.00004891737],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000009545271,0.0004400379,0.003242477,0.0002871898,0.00009558004,0.000001222717,0.2093971,0.000011057,0.02362021,0.3268632,0.120593,0.3154393],"study_design_scores_gemma":[0.0003307324,0.0001115862,0.001955581,0.0000127212,0.000002581322,0.0000197864,0.0006652123,0.8653337,0.002587765,0.006892234,0.1219267,0.0001613348],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3622642,0.00008807934,0.629661,0.003385783,0.0006395092,0.001058895,0.000001046812,0.000227265,0.002674297],"genre_scores_gemma":[0.9930404,0.000002958104,0.003622668,0.0003360713,0.00002494454,0.0001552197,9.836797e-7,0.000002595733,0.002814177],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8653227,"threshold_uncertainty_score":0.2120126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01287094194968495,"score_gpt":0.2541684388752869,"score_spread":0.241297496925602,"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."}}