{"id":"W6888351780","doi":"10.21227/3x6d-3v62","title":"RGB Images from Wearable Cameras: Applications for Environment Recognition and Lower-Limb Biomechatronic Device Control","year":2019,"lang":"en","type":"dataset","venue":"IEEE DataPort","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"RGB color model; Wearable computer; Wearable technology; Robot vision; Robotics; Assistive device; Image (mathematics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0009004145,0.005016806,0.002058637,0.004420231,0.0009671822,0.001564854,0.003832975,0.002320638,0.01244743],"category_scores_gemma":[0.002176747,0.000749645,0.001881693,0.004415164,0.0005963563,0.001230747,0.002735174,0.001811125,0.03076048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001501048,"about_ca_system_score_gemma":0.001639674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03137969,"about_ca_topic_score_gemma":0.06068537,"domain_scores_codex":[0.9982606,0.0001689791,0.0001792463,0.0004319944,0.0006140799,0.0003452222],"domain_scores_gemma":[0.9988425,0.0001004808,0.000105348,0.0003664745,0.0004823469,0.0001028021],"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":[0.000539744,0.0003953501,0.003327758,0.001963316,0.000152454,0.0002956261,0.00006092032,0.001783312,0.00428334,0.0004375255,0.9307553,0.05600535],"study_design_scores_gemma":[0.0005284038,0.0004072738,0.06244788,0.001187222,0.0002650429,0.001867744,0.0006920968,0.0166795,0.02507499,0.002866353,0.8876438,0.0003395109],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.005970785,0.001167091,0.003287396,0.0002194452,0.0003317511,0.0003238455,0.9805881,0.004801982,0.003309571],"genre_scores_gemma":[0.004901157,0.0002670825,0.003828952,0.00005672108,0.00002617637,0.000290987,0.989055,0.0001233719,0.001450521],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03137969,"threshold_uncertainty_score":0.06239408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0357027288794738,"score_gpt":0.2738860387685259,"score_spread":0.2381833098890521,"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."}}