MétaCan
Menu
Back to cohort

Commercial Form Analysis and Strategy Optimization of Train Station Based on Urban Development

2014· article· en· W2023165105 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

VenueApplied Mechanics and Materials · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicEvaluation Methods in Various Fields
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsTerminal (telecommunication)Transport engineeringSpace (punctuation)EngineeringDevelopment (topology)Scale (ratio)Civil engineeringComputer scienceTelecommunicationsGeography

Abstract

fetched live from OpenAlex

This paper studied commercial space of the Shanghai Railway Station. It summed up construction and development of history railway and railway passenger transportation. It clarified commercial activities of major railway terminal. It summarized appropriate scale and location of different business activities by the tightness of characteristics different commercial activities as well as problems and deficiencies of existing large passenger commercial space. It identified the source of the problem by several field researches on Shanghai Railway Station. This paper summarized different layout features of the passenger terminal commercial space design history and analyzed the differences and reasons. Finally this paper presented specific strategies and ideas of a large railway passenger commercial space design combined with their views of trends for railway passenger comprehensive development.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.603
Threshold uncertainty score0.564

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.267
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