{"id":"W2395465087","doi":"10.1145/2858036.2858052","title":"DualKey","year":2016,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Selection (genetic algorithm); Process (computing); Term (time); Artificial intelligence; Key (lock); Identification (biology); Computer vision; Machine learning; Operating system","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":[0.0007809235,0.001110406,0.0008674738,0.0008904893,0.0004248435,0.001771978,0.002544205,0.0007690383,0.1114847],"category_scores_gemma":[0.003227895,0.0006711973,0.0005868482,0.000487942,0.0005066033,0.003981636,0.003150793,0.0007190285,0.05071395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002898197,"about_ca_system_score_gemma":0.0004056623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003170557,"about_ca_topic_score_gemma":0.0006027834,"domain_scores_codex":[0.9992067,0.00007091262,0.00007259801,0.000300184,0.000228206,0.0001214439],"domain_scores_gemma":[0.9982681,0.0004484653,0.0001263492,0.0005617799,0.0003819464,0.0002132758],"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":[0.005642515,0.0003589696,0.004572969,0.00272018,0.0001753183,0.0007278593,0.0007669245,0.0006131904,0.1967504,0.01359727,0.1040474,0.6700271],"study_design_scores_gemma":[0.0006645774,0.00326063,0.02348867,0.0006565329,0.0003270191,0.00924378,0.0006661008,0.009004748,0.1623354,0.009224293,0.7808164,0.0003118705],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.2143749,0.007495748,0.4804775,0.001531457,0.003628055,0.00143712,0.01403006,0.05719943,0.2198259],"genre_scores_gemma":[0.4579465,0.003529407,0.24651,0.001341391,0.0003923385,0.001527007,0.01213943,0.01107411,0.2655398],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1114847,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008056093002512487,"score_gpt":0.2250448472566883,"score_spread":0.2169887542541759,"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."}}