{"id":"W2276615213","doi":"","title":"Two perspectives on learning rich representations from robot experience","year":2013,"lang":"en","type":"article","venue":"","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Robot; Artificial intelligence; Computer science; Space (punctuation); Robot learning; Position (finance); Social robot; Human–computer interaction; Mobile robot; Robot control","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":["insufficient_payload"],"category_scores_codex":[0.00007481891,0.0001317658,0.0001119509,0.00009328877,0.0002477325,0.0004495427,0.0007557216,0.00003171359,0.0009538542],"category_scores_gemma":[0.0002437726,0.0001161169,0.00004447125,0.0003327187,0.00005905779,0.0008965994,0.0002575469,0.0002462112,0.001653233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005523037,"about_ca_system_score_gemma":0.00002319645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008407542,"about_ca_topic_score_gemma":0.000003013381,"domain_scores_codex":[0.9985935,0.0000910298,0.0001955804,0.0004866922,0.0003672892,0.0002658816],"domain_scores_gemma":[0.9987664,0.0002973574,0.00008986133,0.0006306382,0.0001242939,0.00009141285],"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":[0.00000112497,0.00002888108,0.006873644,7.377924e-7,0.00001541143,0.000002962409,0.02200443,0.9136267,0.001959774,0.05331903,0.000623364,0.001543917],"study_design_scores_gemma":[0.000340878,0.0001288059,0.02389549,0.00001445736,0.000003321474,0.000002268454,0.01550502,0.9554467,0.003032715,0.000835702,0.0005016816,0.0002930023],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05691765,0.00002186875,0.8757645,0.0007321624,0.0001735568,0.0001598536,7.809998e-8,0.0003579782,0.0658723],"genre_scores_gemma":[0.8746098,0.00001075376,0.1166156,0.0002081179,0.00006364075,0.00004352874,0.000002167261,0.000008753337,0.008437634],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8176922,"threshold_uncertainty_score":0.9999594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02188573679674652,"score_gpt":0.2941732647110618,"score_spread":0.2722875279143152,"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."}}