{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000294707,0.0007449225,0.0004729412,0.0002923635,0.001339751,0.001816419,0.000718499,0.00126523,0.1145855],"category_scores_gemma":[0.0006431144,0.0001765328,0.000281087,0.0006135546,0.0004366889,0.001661186,0.003090833,0.000540227,0.01509026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003408002,"about_ca_system_score_gemma":0.0003773937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002212543,"about_ca_topic_score_gemma":0.006205902,"domain_scores_codex":[0.9998366,0.0000681456,0.000004515424,0.00002944306,0.0000266506,0.00003458091],"domain_scores_gemma":[0.9997141,0.00007362274,0.000009777143,0.0000282275,0.00004893889,0.0001253384],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002314136,0.0003472779,0.004052521,0.001007941,0.00005479819,0.005242297,0.007182807,0.003155026,0.02871023,0.01038044,0.6407592,0.2967933],"study_design_scores_gemma":[0.0001929504,0.00074734,0.01335201,0.0005021506,0.0001124319,0.004929552,0.01202355,0.01383157,0.009238425,0.006974168,0.9378918,0.0002039666],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2603743,0.005241533,0.1704366,0.01071302,0.00265615,0.001341167,0.03406489,0.04312707,0.4720452],"genre_scores_gemma":[0.6398962,0.00326327,0.0586349,0.002184531,0.001163999,0.001128216,0.01240049,0.002353898,0.2789745],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1145855,"threshold_uncertainty_score":0.3833266,"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."}}