{"id":"W2518480459","doi":"10.1145/2971763.2971786","title":"Grabbing at an angle","year":2016,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"RWTH Aachen University; Natural Sciences and Engineering Research Council of Canada; Centre for Interdisciplinary Research in Music Media and Technology; Faculty of Engineering, McGill University","keywords":"Workload; Computer science; Textile; Selection (genetic algorithm); Computer vision; Artificial intelligence; Simulation; Materials science; Composite material","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00004242785,0.00004422806,0.00003779696,0.00002794099,0.00005915333,0.00002458763,0.0002991394,0.00001299582,0.0002961818],"category_scores_gemma":[0.000009522862,0.00002489118,0.00002607885,0.00005186228,0.00001191955,0.0008392665,0.0001323125,0.0000141552,0.0009376354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003314015,"about_ca_system_score_gemma":0.000006751661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001277606,"about_ca_topic_score_gemma":0.00001097119,"domain_scores_codex":[0.9995744,0.00001662046,0.00004738006,0.0001630461,0.00006750143,0.0001311118],"domain_scores_gemma":[0.9996325,0.0000304974,0.00001594341,0.0002353933,0.00004066269,0.00004495404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000004527704,0.00002976816,0.001948455,6.58264e-7,0.000005867204,0.00000798913,0.0002586832,1.723719e-7,0.7693171,0.2083048,0.00831823,0.0118038],"study_design_scores_gemma":[0.0003443783,0.000180824,0.0278633,0.00001210539,0.000001778203,0.00002209413,0.00005606334,0.0008121722,0.9371912,0.003832307,0.02947518,0.0002085565],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1663528,0.000007939392,0.7512805,0.001330516,0.0002866383,0.00003496918,7.417954e-7,0.00003523039,0.08067068],"genre_scores_gemma":[0.9884332,0.000001535257,0.001635788,0.0008502767,0.00002730882,0.000001799186,3.509999e-7,0.000002481803,0.009047203],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8220805,"threshold_uncertainty_score":0.9998403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01658281238653292,"score_gpt":0.252981784349653,"score_spread":0.2363989719631201,"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."}}