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Record W4234659313 · doi:10.22217/upi.2019.396

老龄人口健身出行视角下的寒地城市公共空间可步行性研究

2019· article· zh· W4234659313 on OpenAlexaboutno aff
Hong Leng, Chunyu Zheng, Yuwen Ru

Bibliographic record

VenueUrban Planning International · 2019
Typearticle
Languagezh
FieldMedicine
TopicDiverse Approaches in Healthcare and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

As China gradually enters an aging society, health issues of elder people grab the attention of whole society. Doing adequate physical activity is beneficial for health of elder people. Better accessibility could increase the utilization of public space, encourage urban residents to participate in physical activity. However, the climate characteristic is a domain factor for winter cities. Although there is a growing number of researches concerning elder people and walkability. However, knowledge gap regarding to climate context exists, especially in winter climate characteristics in cold region. This paper takes Harbin, a typical winter city of China, as research site, analyzes the current situation of public space walkability according to the physical activity behaviors and travel behaviors of elder people. Based on it, combined with the experience of cold cities in North America such as Ottawa and with the walkability status of winter cities in China, strategies including reallocating spatial distribution of public spaces, constructing comprehensive walking system and creating enjoyable walking environment to improve and optimize the walkability of urban public space are proposed.

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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.558
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0070.007

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 head0.081
GPT teacher head0.359
Teacher spread0.278 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2019
Admission routes1
Has abstractyes

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