{"id":"W2395549257","doi":"10.4230/dagsemproc.10081.1","title":"10081 Abstracts Collection – Cognitive Robotics","year":2010,"lang":"en","type":"article","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Robotics and Automated Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Informatics; Robotics; Computer science; Artificial intelligence; Cognitive robotics; Cognition; Section (typography); Research center; Cognitive science; Robot; Psychology; Engineering; Medicine; Electrical engineering; Neuroscience","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":[0.0003477637,0.0004012971,0.000421377,0.000254748,0.000285626,0.0003275155,0.0003053746,0.000399846,0.00004909937],"category_scores_gemma":[0.00008900689,0.0003913749,0.0001906778,0.0002936978,0.00007802757,0.0006677175,0.00005947111,0.0007077975,0.0003764706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000816475,"about_ca_system_score_gemma":0.00004633882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001222054,"about_ca_topic_score_gemma":0.00007752154,"domain_scores_codex":[0.9977131,0.00001134447,0.001077487,0.0001675267,0.0003467283,0.0006837784],"domain_scores_gemma":[0.9987638,0.0001342578,0.0002262108,0.0003592922,0.0002863868,0.0002300568],"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":[0.0005027647,0.0020401,0.01903378,0.01037261,0.003877218,0.00009808027,0.03904786,0.7148946,0.02328372,0.0153841,0.136065,0.03540019],"study_design_scores_gemma":[0.004555606,0.000243377,0.004417554,0.0003888193,0.0001502972,0.0002257779,0.001862109,0.9255171,0.01108136,0.0003120526,0.04988112,0.001364791],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8569283,0.00006030158,0.0702569,0.0001417935,0.01029564,0.002524708,0.0007743515,0.001819276,0.05719869],"genre_scores_gemma":[0.9926776,0.00002625129,0.005766786,0.0001219431,0.0002998215,0.00008674611,0.0004544404,0.00009904983,0.0004673876],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2106225,"threshold_uncertainty_score":0.9998538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008313654482951193,"score_gpt":0.2228798340087242,"score_spread":0.2145661795257731,"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."}}