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Record W2134740088 · doi:10.1155/2012/264295

Research on the Behavior Characteristics of Pedestrian Crowd Weaving Flow in Transport Terminal

2012· article· en· W2134740088 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMathematical Problems in Engineering · 2012
Typearticle
Languageen
FieldEngineering
TopicEvacuation and Crowd Dynamics
Canadian institutionsTransport Canada
FundersNational Key Research and Development Program of ChinaBeijing Municipal Natural Science FoundationNational Natural Science Foundation of China
KeywordsWeavingPedestrianStairsTerminal (telecommunication)Transport engineeringComputer scienceGRASPEngineeringSimulationArchitectural engineeringCivil engineeringTelecommunicationsMechanical engineering

Abstract

fetched live from OpenAlex

Due to the poor transfer organization in urban public transport terminal, pedestrian crowd are often forced to weaving in their transfer flow lines. Frequent weaving behaviors not only decrease passengers’ transfer comfort, but may also trigger serious crowd disaster such as trampling. In order to get accurate understanding of the weaving features of pedestrian crowd and analyze the relevant evolution law, researches have been conducted on the basis of field investigation. First, the typical weaving phenomenon were defined and classified, and a microscopic parameters system of pedestrian crowd weaving flow was constructed. The detection and quantification methods of multiple indicator parameters were also given. Then, correlation between different behavioral parameters was analyzed based on the survey data of weaving pedestrian crowd on the stairs of DongZhiMen (DZM) hub. The basic characteristics and evolution law of the weaving behaviors were then discussed, and conclusions were drawn.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.497

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.048
GPT teacher head0.295
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it