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Record W7084156551 · doi:10.5149/9781469687933_powers

Cataloochee: Lost Settlement of the Smokies

2025· book· en· W7084156551 on OpenAlexaboutno aff

Bibliographic record

VenueWestern Carolina University, Hunter Library eBooks · 2025
Typebook
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Identification and Susceptibility Testing
Canadian institutionsnot available
Fundersnot available
KeywordsSettlement (finance)WildlifePopulationHuman settlementNational park

Abstract

fetched live from OpenAlex

There is a buzz of excitement in Cataloochee these days. Visitors come into this section of the Great Smoky Mountains National Park by the thousands to view the majestic elk and other wildlife roaming the valley. However, there were no elk in Cataloochee for almost 200 years. European settlers arrived in North Carolina in 1587 and the Eastern Elk was hunted to extinction in the 1790s. Fortunately, elk were successfully reintroduced (from Kentucky and Canada) into Cataloochee in 2001 and appear to be on a path to success. But what about the people? What about the Cataloochans who arrived after the elk? The valley has always been difficult to access and the people who came to the valley and settled it in the 1800s were made of sterner stuff than most. What happened to this settlement in the beautiful, remote Cataloochee Valley, which at one time boasted over 1200 residents and was the largest settlement in the Smokies? This is their story ... as told by them.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.342
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 science0.0010.001
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 head0.008
GPT teacher head0.195
Teacher spread0.187 · 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
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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