{"id":"W2991567876","doi":"","title":"Predicting vehicle behaviour using LSTMs and a vector power representation for spatial positions","year":2019,"lang":"en","type":"article","venue":"The European Symposium on Artificial Neural Networks","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Task (project management); Representation (politics); Artificial intelligence; Spatial analysis; Power (physics); Machine learning; Computer vision; Engineering; Remote sensing; Systems engineering; Geography","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":[0.0002888165,0.000660092,0.0004019804,0.0004874955,0.0001811825,0.0005929213,0.0008245006,0.0006799978,0.001513094],"category_scores_gemma":[0.00129003,0.0003670524,0.0004496179,0.0007206612,0.0003125279,0.001648748,0.0006017101,0.0009983316,0.0007608149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000472941,"about_ca_system_score_gemma":0.0004740962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007434359,"about_ca_topic_score_gemma":0.009577516,"domain_scores_codex":[0.9998463,0.00002623592,0.00001069872,0.00006016818,0.00002956055,0.00002695117],"domain_scores_gemma":[0.9997142,0.00009432158,0.00004446463,0.00004436509,0.000085108,0.000017574],"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":[0.0001717567,0.000198187,0.004749703,0.0001107651,0.000127765,0.0001768352,0.0001477825,0.5935505,0.02148507,0.007293968,0.003626706,0.3683611],"study_design_scores_gemma":[0.000002086134,0.00002014151,0.0004813036,0.000005449408,0.000008115166,0.00001285786,0.000009601341,0.9953675,0.001142635,0.002671705,0.0002739521,0.00000460093],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08208028,0.000343078,0.911512,0.0005444721,0.0002858392,0.00003426172,0.0006027814,0.0018242,0.00277327],"genre_scores_gemma":[0.9070485,0.0002985105,0.08847541,0.000142011,0.00008490706,0.00005689572,0.0007155011,0.00007496695,0.003103231],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007434359,"threshold_uncertainty_score":0.01478219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01368452148302297,"score_gpt":0.2289709085938224,"score_spread":0.2152863871107994,"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."}}