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Fiscal and Economic Impact Analysis of Proposed Nexus Natural Gas Pipeline on the City of Green, Ohio: A Case Study

2017· article· en· W2784855116 on OpenAlexaboutno aff
Robert A. Simons, Andrew R. Thomas, Iryna Lendel, Bryan Townley

Bibliographic record

VenueJournal of Sustainable Real Estate · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsNexus (standard)Pipeline (software)Natural gasRevenueTax revenueNatural resource economicsEconomicsEconomyBusinessEngineeringFinancePublic economicsWaste management

Abstract

fetched live from OpenAlex

In order to provide a sustainable outlet for natural gas harvested from the fracking fields of eastern Ohio, in 2015 Nexus announced plans to build 250 miles of high-pressure natural gas transmission pipeline that would run from the source into Michigan, ultimately to Ontario, Canada. The pipeline route passes through the fast-growing City of Green, Ohio, and could disrupt development plans there. The proposed path would cause the City of Green to disproportionately bear the burden of anticipated economic losses and reduction in tax revenue associated with the pipeline. Despite substantial front-loaded ad valorem taxes paid by the pipeline utility, over a 50-year period, the pipeline is projected to cause NPV fiscal losses of over $52 million, largely from foregone property and income taxes for future 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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.293
Threshold uncertainty score0.583

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.009
GPT teacher head0.262
Teacher spread0.253 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2017
Admission routes1
Has abstractyes

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