{"id":"W4401415287","doi":"10.1109/icra57147.2024.10611477","title":"Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration<sup>0</sup>","year":2024,"lang":"en","type":"article","venue":"","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":124,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Computer graphics (images); Artificial intelligence; Human–computer interaction","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003951158,0.003136015,0.0009159445,0.001532753,0.0009819794,0.002281343,0.004818335,0.003125092,0.01247277],"category_scores_gemma":[0.01298123,0.001027757,0.002631191,0.002056166,0.001695332,0.003246661,0.00533936,0.003620502,0.01405484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001468164,"about_ca_system_score_gemma":0.002007918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01254884,"about_ca_topic_score_gemma":0.02054965,"domain_scores_codex":[0.9973218,0.0006351555,0.0002259392,0.0009907663,0.0005889444,0.0002373954],"domain_scores_gemma":[0.9947146,0.001349064,0.0003382975,0.002634713,0.0005910393,0.0003723181],"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":[0.001637093,0.00147276,0.01432382,0.001980929,0.0006229272,0.000579391,0.0004246194,0.06136258,0.004283505,0.009166935,0.7306776,0.1734678],"study_design_scores_gemma":[0.001133308,0.001805747,0.02608917,0.0006670731,0.0002543,0.001424076,0.0008227424,0.3273302,0.02910843,0.03200065,0.5789691,0.0003950947],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.118859,0.00556119,0.1676964,0.00509782,0.002505683,0.001748001,0.5123869,0.1576018,0.0285433],"genre_scores_gemma":[0.0983464,0.000875734,0.1309792,0.0009702083,0.0001597303,0.001377128,0.7548231,0.003392959,0.009075584],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01254884,"threshold_uncertainty_score":0.04172558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03703542100640457,"score_gpt":0.293806474642293,"score_spread":0.2567710536358885,"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."}}