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Record W2795716466 · doi:10.1155/2018/1767149

The Impact of Urban Transit Systems on Property Values: A Model and Some Evidences from the City of Naples

2018· article· en· W2795716466 on OpenAlexvenueno aff
Mariano Gallo

Bibliographic record

VenueJournal of Advanced Transportation · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsEurosReal estateProperty valueTransit (satellite)Transport engineeringLand ValuesResidential real estateLight rail transitRapid transitProperty (philosophy)Transit systemValue (mathematics)Hedonic pricingBusinessCivil engineeringComputer scienceEconometricsEngineeringPublic transportEconomicsFinanceLand use

Abstract

fetched live from OpenAlex

A hedonic model for estimating the effects of transit systems on real estate values is specified and calibrated for the city of Naples. The model is used to estimate the external benefits concerning property values which may be attributed to the Naples metro at the present time and in two future scenarios. The results show that only high-frequency metro lines have appreciable effects on real estate values, while low-frequency metro lines and bus lines produce no significant impacts. Our results show that the impacts on real estate values of the metro system in Naples are significant, with corresponding external benefits estimated at about 7.2 billion euros or about 8.5% of the total value of real estate assets.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.516
Threshold uncertainty score0.199

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)0.0000.000

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 head0.037
GPT teacher head0.249
Teacher spread0.212 · 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

Citations38
Published2018
Admission routes1
Has abstractyes

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