{"id":"W2982374885","doi":"10.1609/aiide.v15i1.5245","title":"Knowledge-Powered Inference of Crowd Behaviors in Semantically Rich Environments","year":2019,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Computer science; Ontology; Human–computer interaction; Inference; Context (archaeology); Graph; Interface (matter); Space (punctuation); Artificial intelligence; Theoretical computer science","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":[0.00009986614,0.0001963981,0.0002556205,0.0001296117,0.00002008283,0.00008539992,0.0003048425,0.00006489416,0.0001104489],"category_scores_gemma":[0.00007961326,0.0001594339,0.00007008313,0.0001627865,0.0001319524,0.000431563,0.0001324841,0.0002125988,0.00005724278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008592862,"about_ca_system_score_gemma":0.00001610128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005463528,"about_ca_topic_score_gemma":0.000006608867,"domain_scores_codex":[0.9988169,0.000006097919,0.0005143008,0.000233235,0.0002282177,0.0002012308],"domain_scores_gemma":[0.9995233,0.00007312792,0.0001379294,0.0001169945,0.0000958112,0.00005287323],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007737888,0.002777183,0.1127144,0.0005593256,0.000222398,0.000001728822,0.01698073,0.002198242,0.5244596,0.1996074,0.00005129239,0.1396539],"study_design_scores_gemma":[0.0002696192,0.0008675107,0.01746948,0.001492582,0.00003554926,0.000003577757,0.009894384,0.1233343,0.8337271,0.01211547,0.0001852923,0.000605143],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9792652,0.00001519851,0.0004686335,0.00006935337,0.00016392,0.0003329081,0.00001528684,0.00001450873,0.01965504],"genre_scores_gemma":[0.9995573,0.00007192043,0.00002409277,0.00002037272,0.000006715204,0.00001744948,0.000002763881,0.00001447533,0.0002849414],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3092674,"threshold_uncertainty_score":0.6501524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02100443612018971,"score_gpt":0.2734229021845426,"score_spread":0.2524184660643529,"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."}}