{"id":"W4387652983","doi":"10.1007/978-981-99-6495-6_36","title":"Decision-Making in Robotic Grasping with Large Language Models","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Robot; Human–computer interaction; Focus (optics); Artificial intelligence; Perception; Action (physics); ENCODE; Task (project management); Systems engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003495663,0.0002764558,0.0003067707,0.0008368922,0.00008216725,0.0001468448,0.0004478175,0.0001609996,0.00002173004],"category_scores_gemma":[0.00004514947,0.0002522075,0.00004144025,0.0005254567,0.00006689014,0.0002365828,0.0001609186,0.0007119823,0.0000351634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001787234,"about_ca_system_score_gemma":0.00005392935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007891492,"about_ca_topic_score_gemma":0.0004284856,"domain_scores_codex":[0.9983675,0.000009291322,0.0002744772,0.000484461,0.000435252,0.0004290541],"domain_scores_gemma":[0.9991778,0.0003316673,0.00005450581,0.0003514885,0.00003333686,0.0000512231],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001981699,0.000002128803,0.00006821011,0.00002762316,0.000003420274,0.0001151276,0.001154379,0.9388216,0.000009041154,0.001137892,0.000001762195,0.05865686],"study_design_scores_gemma":[0.0001363262,0.00001665293,0.0003592373,0.001467348,0.000003082132,0.00001311184,0.000001513964,0.9831745,0.000007439681,0.01450371,0.0000110439,0.0003060499],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0004473995,0.0002300557,0.996277,0.00002253661,0.0005849724,0.0001601788,2.173766e-7,0.0002678748,0.00200979],"genre_scores_gemma":[0.9452513,0.00001374864,0.05430104,0.0001295746,0.0001283281,0.000003381041,0.000003352233,0.00006940297,0.00009982265],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.944804,"threshold_uncertainty_score":0.999993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01886303579593853,"score_gpt":0.2510509425887102,"score_spread":0.2321879067927717,"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."}}