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Record W2266198135 · doi:10.5539/jsd.v9n1p132

Urban Form and Microclimatic Conditions in Urban Open Spaces at the Densely Built Centre of a Greek City

2016· article· en· W2266198135 on OpenAlexvenueno aff
Maria Makropoulou, Aspa Gospodini

Bibliographic record

VenueJournal of Sustainable Development · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Heat Island Mitigation
Canadian institutionsnot available
Fundersnot available
KeywordsMicroclimateCity blockCanyonPublic spaceUrban morphologyUrban designStreet canyonEnvironmental scienceRelative humidityGeographyBlock (permutation group theory)Urban planningCivil engineeringPhysical geographyMeteorologyArchitectural engineeringCartographyArchaeologyMathematicsEngineeringGeometry

Abstract

fetched live from OpenAlex

The paper presents an experimental investigation of the microclimatic conditions in selected open spaces in the city centre of Volos, a medium-sized coastal city in Greece. It presents the results of systematic field measurements that took place in three urban sites; a public open space and two typical urban blocks. The measurements were carried out during the summer of 2013 and concerned air temperature and relative humidity recordings. Data collection was used to assess the formation and the eventual differentiation of microclimate on a restricted local scale in the urban environment, such as that of a typical urban block or/and a typical public square in the centre of Greek cities. Additionally, research has taken into account buildings construction materials, the predominant paving materials and the key parameters determined by urban geometry in the selected sites, i.e the Aspect Ratio (H/W) and the Sky View Factor (SVF). The measurements revealed microclimatic differences within the inside open space of two of the urban blocks, i.e the courtyard generated of the different building ownerships, the various street canyons and the recordings of the local meteorological station.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.568

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 head0.012
GPT teacher head0.227
Teacher spread0.215 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2016
Admission routes1
Has abstractyes

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