{"id":"W53323940","doi":"","title":"Hand-Eye: A Vision-Based Approach to Data Glove Calibration","year":2000,"lang":"en","type":"article","venue":"","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Wired glove; Computer vision; Computer science; Artificial intelligence; Feature (linguistics); Calibration; Filter (signal processing); Personalization; Mathematics","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":[0.0003365707,0.0001043678,0.0001231155,0.00007343847,0.00009345497,0.0004636028,0.001077831,0.00005565594,0.0002995055],"category_scores_gemma":[0.00002138798,0.00008118588,0.00002487854,0.0004922666,0.00001602966,0.0006730266,0.0001275604,0.00005610619,0.0009020152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001575624,"about_ca_system_score_gemma":0.00006868152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005840427,"about_ca_topic_score_gemma":0.0000158609,"domain_scores_codex":[0.9986785,0.00009104137,0.0002018006,0.0005306023,0.0003164768,0.0001815875],"domain_scores_gemma":[0.998544,0.00005276979,0.00002692231,0.00118052,0.00004582418,0.0001498967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003667595,0.0006397592,0.0002853502,0.00005609138,0.00003313626,0.00001169057,0.001348327,0.003395309,0.001411239,0.004684317,0.1950399,0.7930582],"study_design_scores_gemma":[0.000314051,0.0000483891,0.0002414627,0.00001675955,0.000002626777,0.000005965157,0.00001242393,0.898297,0.0009936963,0.00009938025,0.09979787,0.0001703661],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0006118415,0.00001746522,0.9288361,0.001669742,0.0001105908,0.0002723698,0.00001534439,0.0001736991,0.06829282],"genre_scores_gemma":[0.8311139,0.0000011357,0.1596932,0.0036433,0.000187136,0.0000322743,0.0001370723,0.00001155655,0.005180489],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8949017,"threshold_uncertainty_score":0.9998759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03743637405613563,"score_gpt":0.2858382076051528,"score_spread":0.2484018335490171,"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."}}