{"id":"W4398184165","doi":"10.1201/9781003488682-34","title":"Crowd Counting for Risk Management Using Deep Learning","year":2024,"lang":"en","type":"book-chapter","venue":"","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Computer science; Artificial intelligence","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":[0.0001899873,0.0001832869,0.0001468094,0.0001671588,0.0003013629,0.0002738249,0.0003932026,0.0001275764,0.00006241522],"category_scores_gemma":[0.000002208698,0.0001793145,0.0001636891,0.00005702089,0.00002073039,0.00009839357,0.0003206568,0.0002729278,0.0001179964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008289742,"about_ca_system_score_gemma":0.00001081908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000138276,"about_ca_topic_score_gemma":0.000004261398,"domain_scores_codex":[0.9989704,0.000003043096,0.0002328535,0.0004844236,0.0001436136,0.0001656423],"domain_scores_gemma":[0.9993545,0.00003674693,0.0001610338,0.0003475969,0.00006406561,0.00003602749],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[3.599133e-7,0.000001822633,7.226021e-7,0.00004481609,0.00003568444,0.000001858149,0.00001334569,0.0001398106,0.00000451906,0.9155886,0.0002949385,0.08387352],"study_design_scores_gemma":[0.00002745309,0.00001989429,6.151926e-7,0.0000524514,0.00005068059,0.000005301092,0.000006007911,0.1889927,0.00005403898,0.1717042,0.6389055,0.0001811353],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[8.816714e-7,0.0001579822,0.574769,0.00002799682,0.00008046487,0.0002557964,0.000001855867,0.0005173411,0.4241886],"genre_scores_gemma":[0.0005732209,0.0002030394,0.3589837,0.00005958353,0.000116144,0.00005976388,0.000003625793,0.00003667213,0.6399642],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7438844,"threshold_uncertainty_score":0.7312232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01879112699367539,"score_gpt":0.2585395558070919,"score_spread":0.2397484288134165,"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."}}