{"id":"W3212534344","doi":"10.48550/arxiv.2111.03635","title":"BBC-Oxford British Sign Language Dataset","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Research (Canada)","funders":"","keywords":"Sign (mathematics); Linguistics; History; Computer science; Natural language processing; Mathematics; Philosophy","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":[0.001004261,0.001976873,0.001820322,0.00408714,0.001485343,0.001664143,0.002428194,0.001925468,0.05362521],"category_scores_gemma":[0.005153422,0.0003812661,0.0007911142,0.004020654,0.0006497177,0.001320111,0.002499572,0.001690761,0.07542761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002044062,"about_ca_system_score_gemma":0.003663373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1204608,"about_ca_topic_score_gemma":0.2237378,"domain_scores_codex":[0.9981602,0.0002796511,0.0001901606,0.0003899316,0.0006821004,0.0002980458],"domain_scores_gemma":[0.9979609,0.0002771344,0.00009047676,0.0004552628,0.0009309822,0.0002851623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001750247,0.00006732768,0.001708207,0.0003769963,0.00002733266,0.0001631248,0.00003955994,0.0003540112,0.0007846442,0.0005118336,0.9740535,0.0217384],"study_design_scores_gemma":[0.0003096891,0.0001194486,0.02481156,0.0004073225,0.00006749163,0.0009087368,0.0005214374,0.006248695,0.002592397,0.001630828,0.9622614,0.0001209918],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.007008615,0.0008062514,0.001387856,0.0003650126,0.0003147867,0.0002428397,0.9759427,0.002650465,0.01128146],"genre_scores_gemma":[0.003756781,0.0001227816,0.001225172,0.00007638676,0.00001759993,0.0002522924,0.9904321,0.00009231259,0.004024538],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1204608,"threshold_uncertainty_score":0.2395194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05956021653571327,"score_gpt":0.1916315840599191,"score_spread":0.1320713675242058,"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."}}