{"id":"W2556282887","doi":"","title":"Handwavey: A Gestural Motion Password Interface","year":2010,"lang":"en","type":"article","venue":"","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Password; Computer science; Dynamic time warping; Motion (physics); Set (abstract data type); Kinesthetic learning; Password strength; Computer security; Cognitive password; Human–computer interaction; One-time password; Biometrics; Artificial intelligence; Programming language; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002419572,0.00009421455,0.000100855,0.00006562663,0.0000636499,0.0002090777,0.0004166063,0.00007362514,0.0001044985],"category_scores_gemma":[0.00003877937,0.00007046253,0.000044021,0.0001989732,0.00002009031,0.000406617,0.0001129834,0.0001969552,0.0008224858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009019026,"about_ca_system_score_gemma":0.00001897816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002721503,"about_ca_topic_score_gemma":0.0001407907,"domain_scores_codex":[0.9992017,0.00004098564,0.0001532048,0.0002521171,0.000174532,0.0001775149],"domain_scores_gemma":[0.9993502,0.00004997444,0.00004308872,0.0003711919,0.00009338004,0.00009215168],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007022059,0.0001437522,0.007565008,0.00002686613,0.00004004335,0.00002132737,0.001939553,0.000008678569,0.0875817,0.06400172,0.01248933,0.826175],"study_design_scores_gemma":[0.003241397,0.0004014424,0.1141944,0.0001328003,0.00002626035,0.001255568,0.0003269098,0.08124028,0.2448093,0.01497604,0.537349,0.002046542],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09462079,0.00001480712,0.8812151,0.00226442,0.001967444,0.0001334973,6.382026e-7,0.0003527892,0.01943051],"genre_scores_gemma":[0.9801991,0.000001101001,0.01687772,0.0002084271,0.0001704558,0.00001216933,0.00000102103,0.000004910976,0.00252511],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8855783,"threshold_uncertainty_score":0.9999555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01100199424066992,"score_gpt":0.2458528376702184,"score_spread":0.2348508434295485,"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."}}