{"id":"W2397344958","doi":"10.1007/978-3-319-21966-0_21","title":"MOVTCHA: A CAPTCHA Based on Human Cognitive and Behavioral Features Analysis","year":2015,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Alberta Innovates - Technology Futures","keywords":"CAPTCHA; Computer science; Usability; Cognition; Artificial intelligence; Human–computer interaction; Matching (statistics); Machine learning","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003384913,0.001071688,0.0005636888,0.0009041818,0.0003427199,0.0006463268,0.001190759,0.000911931,0.009423319],"category_scores_gemma":[0.002011658,0.0002778786,0.0006836454,0.0006744945,0.0004075022,0.000925235,0.000986823,0.001029902,0.003674137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002597673,"about_ca_system_score_gemma":0.0003736966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001360015,"about_ca_topic_score_gemma":0.001383187,"domain_scores_codex":[0.9996091,0.00005924062,0.00001485602,0.00009692497,0.0001839456,0.00003597751],"domain_scores_gemma":[0.9992942,0.0002938506,0.00005124784,0.0001258031,0.0001941963,0.00004081196],"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":[0.0006340666,0.000145851,0.0006886983,0.0003135919,0.000074983,0.0002449457,0.0001904045,0.01439983,0.09118833,0.005451874,0.01702092,0.8696465],"study_design_scores_gemma":[0.00009186441,0.0005298025,0.004139537,0.0001146085,0.0001372931,0.001164616,0.0001280315,0.8102958,0.1252376,0.01148378,0.04653029,0.000146751],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01003423,0.0003639191,0.9704571,0.00009289301,0.0002325815,0.0001784053,0.0004598037,0.01236578,0.005815245],"genre_scores_gemma":[0.2519503,0.0006019534,0.7282367,0.0004008957,0.000199749,0.000529021,0.002191626,0.001666542,0.01422321],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009423319,"threshold_uncertainty_score":0.03152412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05095114200287299,"score_gpt":0.319930769796148,"score_spread":0.268979627793275,"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."}}