{"id":"W2998392846","doi":"","title":"HoME: a Household Multimodal Environment.","year":2018,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Multimodal Machine Learning Applications","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Université de Sherbrooke","funders":"","keywords":"Computer science; Generalization; Human–computer interaction; Robotics; Context (archaeology); Semantics (computer science); Reinforcement learning; Artificial intelligence; Transfer of learning; Multimodal interaction; Robot; Programming language","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":[],"consensus_categories":[],"category_scores_codex":[0.002435743,0.0002222534,0.0001870668,0.0001509187,0.0005725223,0.0003448807,0.002071562,0.0001083036,0.0001541545],"category_scores_gemma":[0.0004386771,0.0002348621,0.0001030265,0.0005087751,0.0003255485,0.0003422947,0.0008750628,0.0003044466,0.0006181675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007876897,"about_ca_system_score_gemma":0.00007877497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001089248,"about_ca_topic_score_gemma":0.0001445541,"domain_scores_codex":[0.996275,0.001847318,0.0003301805,0.0007511754,0.0004000251,0.0003962899],"domain_scores_gemma":[0.9957867,0.000759474,0.0002258344,0.002561033,0.0004494103,0.0002175191],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000009619565,0.001196121,0.02069181,0.00002936974,0.00006518979,0.000006341505,0.01373928,0.0002035209,0.02520838,0.6731786,0.00202029,0.2636515],"study_design_scores_gemma":[0.00180698,0.000002854146,0.1813269,0.000274648,0.00002867536,0.00004738564,0.0000553582,0.6346037,0.07871157,0.01068132,0.09134217,0.001118439],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1680132,0.00008909575,0.7974841,0.01039161,0.00008567278,0.0002360887,0.00001014251,0.0005638326,0.02312628],"genre_scores_gemma":[0.7285982,0.00002946864,0.2688212,0.0001773686,0.00002823146,0.00004849095,0.00002114883,0.00002422045,0.002251722],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6624972,"threshold_uncertainty_score":0.95774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01118246226324363,"score_gpt":0.2181082726215863,"score_spread":0.2069258103583426,"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."}}