{"id":"W1829026807","doi":"10.1139/l11-073","title":"Gaussian background mixture model based automatic incident detection system for real-time tracking","year":2011,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Detector; Mixture model; Tracking (education); Computer science; Gaussian; Tracking system; Gaussian network model; Incident management; Computer vision; Real-time computing; Artificial intelligence; Kalman filter; Physics; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0005920375,0.0004812392,0.0007763081,0.0008769362,0.0004393585,0.0006547721,0.001089436,0.0007858154,0.004427148],"category_scores_gemma":[0.0005837459,0.0004144496,0.0004382419,0.0006861538,0.0001914477,0.0007575756,0.0005273768,0.0007865716,0.003965744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004429617,"about_ca_system_score_gemma":0.0006682198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003314495,"about_ca_topic_score_gemma":0.00519595,"domain_scores_codex":[0.9996526,0.00004752274,0.00001211014,0.00009527204,0.0001562461,0.00003622352],"domain_scores_gemma":[0.9996779,0.00004698138,0.00002508638,0.00005019653,0.0001757027,0.00002412757],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008924001,0.000570469,0.003329487,0.0001556134,0.0001454618,0.0001915081,0.0001415192,0.04339024,0.2173214,0.004281805,0.02593911,0.7036409],"study_design_scores_gemma":[0.00004308451,0.0001114104,0.002487462,0.00001087935,0.00005385507,0.0001440074,0.00001453221,0.9326647,0.05579773,0.0007974,0.00781094,0.00006403645],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01633852,0.0001620185,0.9677106,0.0001180738,0.000143281,0.00004500876,0.0002273678,0.01242386,0.002831284],"genre_scores_gemma":[0.3984718,0.0002974543,0.5814646,0.0003415754,0.00007498376,0.0001426704,0.001407505,0.000502625,0.01729667],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004427148,"threshold_uncertainty_score":0.01481026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01453530313886496,"score_gpt":0.1911712952518014,"score_spread":0.1766359921129365,"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."}}