{"id":"W2148833817","doi":"10.1145/1073368.1073414","title":"Helping hand","year":2005,"lang":"en","type":"article","venue":"","topic":"Human Motion and Animation","field":"Engineering","cited_by":88,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Inverse kinematics; Motion (physics); Kinematics; Set (abstract data type); Inverse dynamics; Visualization; Position (finance); Artificial intelligence; Computer vision; Robot","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":[0.00001151054,0.00001553195,0.00001367199,0.00001218887,0.00001435776,0.00001479266,0.00001017648,0.000007259242,0.0010184],"category_scores_gemma":[8.467714e-7,0.00001464091,0.000005759639,0.00001308081,0.000002060606,0.00004791297,0.0000011792,0.00001335306,0.0006786309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007203801,"about_ca_system_score_gemma":4.208964e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.621415e-7,"about_ca_topic_score_gemma":0.000006646763,"domain_scores_codex":[0.999907,7.409217e-7,0.00002744298,0.00001588463,0.00001727978,0.00003168966],"domain_scores_gemma":[0.999965,0.000001219423,0.000001098221,0.00001961045,0.000002491415,0.00001065603],"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":[0.00000116118,0.00002581425,0.0002945682,0.00006047538,0.00002117407,0.000001208065,0.001721471,0.1124529,0.2251808,0.04824303,0.08155807,0.5304393],"study_design_scores_gemma":[0.0001941094,0.000005084438,0.004115534,0.000009829965,0.000001525259,0.000001955773,0.00003773363,0.4991554,0.05095964,0.0001220567,0.4452861,0.0001109736],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4305993,0.00006120434,0.1300618,0.0002500993,0.00008234211,0.00002953323,2.30881e-7,0.000515938,0.4383996],"genre_scores_gemma":[0.9966097,0.000003051372,0.001155564,0.0000764542,0.00007429261,5.296019e-7,6.366078e-7,0.00000295114,0.002076747],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5660105,"threshold_uncertainty_score":0.9998948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01105175584183847,"score_gpt":0.2027431907479626,"score_spread":0.1916914349061241,"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."}}