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Record W6992808599

Morgantown MSA Economic Monitor January 2005

2005· article· en· W6992808599 on OpenAlexaboutno aff

Bibliographic record

VenueThe Research Repository @ WVU (West Virginia University) · 2005
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsWest virginiaValue (mathematics)PopulationPresent valueQuarter (Canadian coin)Interest rate
DOInot available

Abstract

fetched live from OpenAlex

Sponsored By Bruceton Bank Morgantown MSA Construction BuildsThe Morgantown MSA posted $104 million in new construction starts in 2003, according to data from FW Dodge, which was up significantly from 2002. 1 Further, the MSA is poised to register another increase in 2004, with the annualized value through the first 11 months of the year at $186 million.That amounts to an estimated $290 million in new construction starts during the last two years.Strong growth in the value of construction starts reflects low interest rates, population growth, and generally optimistic sentiment regarding the future of the region.Indeed, with many other large projects currently proposed (for example, a large new power plant, major retail expansions, additional hospital and medical research facilities, expansion and renovation of WVU facilities and other projects) 2 there will likely be strong construction activity in the region during the next few years.Residential construction has posted strong gains since 2001, as Figure 1 shows.At an annualized rate through the first 11 months of the year, the value of residential construction contracts has increased to $39.2 million from an annual rate $15.9 million in 2003.The reason for this large jump is due to $18.9 million of construction on apartments in Monongalia County.The value of construction for one-family houses increased as well from 2003 to 2004.

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)0.002
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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.827
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.006

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 head0.039
GPT teacher head0.247
Teacher spread0.208 · 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.

Study designNot applicable
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

Citations0
Published2005
Admission routes1
Has abstractyes

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