{"id":"W4297688052","doi":"10.1093/jcde/qwac084","title":"TransNav: spatial sequential transformer network for visual navigation","year":2022,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Multimodal Machine Learning Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; Ministry of Natural Resources","keywords":"Computer science; Reinforcement learning; Artificial intelligence; Inference; Transformer; Machine learning; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003195263,0.001073774,0.0006983482,0.0005276091,0.000309045,0.0005803832,0.002061954,0.0008567619,0.004898005],"category_scores_gemma":[0.001216274,0.0004125416,0.0006788339,0.0005375145,0.0004949112,0.001330895,0.0009793605,0.001411134,0.001005938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001089311,"about_ca_system_score_gemma":0.001411871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02459667,"about_ca_topic_score_gemma":0.02723665,"domain_scores_codex":[0.9998435,0.00002277761,0.000006709375,0.00006133805,0.00003465881,0.00003106262],"domain_scores_gemma":[0.9997619,0.00007494335,0.00002201247,0.00004147042,0.0000697358,0.00002990599],"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":[0.0003791875,0.0001932914,0.001796857,0.0001702004,0.000100821,0.0001726438,0.0000688619,0.6873364,0.00675053,0.01381204,0.01700461,0.2722146],"study_design_scores_gemma":[0.00001050112,0.00002339559,0.00007843586,0.000005310048,0.000007492076,0.00001345006,0.000004390294,0.9937831,0.0009698616,0.004350415,0.0007494688,0.000004132048],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06758702,0.001611855,0.9036824,0.0006712142,0.0003337302,0.0001287197,0.002129746,0.0143398,0.009515453],"genre_scores_gemma":[0.8376848,0.0007028612,0.1441861,0.0003794252,0.00006721703,0.0001959444,0.004014095,0.0004470628,0.01232253],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02459667,"threshold_uncertainty_score":0.04890698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0128942149528395,"score_gpt":0.2588550867853863,"score_spread":0.2459608718325468,"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."}}