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Record W2009607101 · doi:10.1656/045.017.0305

Bog Turtle Habitat on the Lake Ontario Coastal Plain of New York State

2010· article· en· W2009607101 on OpenAlexaboutno aff
Peter A. Rosenbaum, Andrew P. Nelson

Bibliographic record

VenueNortheastern Naturalist · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicTurtle Biology and Conservation
Canadian institutionsnot available
FundersNatural Resources Conservation ServiceU.S. Fish and Wildlife ServiceNew York State Department of Environmental Conservation
KeywordsBogTurtle (robot)SwampHabitatCoastal plainEcologyGeographyWetlandFisheryPeatBiology

Abstract

fetched live from OpenAlex

We develop a concept of suitable habitat for Glyptemys (Clemmys) muhlenbergii (Bog Turtle) on the Lake Ontario Coastal Plain of central and western New York State and compare it to habitat for this species in other parts of its distribution. At the outset of our studies in 1987, only a single Bog Turtle population was known to survive on the Lake Ontario Plain. We located and visited nine of the 10 historically recorded Bog Turtle sites in northern, central and western New York and completed a survey of 84 selected wetlands in Oswego County, at the eastern end of the Lake Plain. In the course of the study, we confirmed the presence of the Bog Turtle at a site where it was last documented in 1916 and discovered populations at three previously undocumented sites, one of which is now the northernmost recorded site for the species. Bog Turtle habitat on the Lake Ontario Coastal Plain is open-canopy, sedge-dominated medium to rich fens contained within larger wetlands that often include an open pond and extensive Acer rubrum (Red Maple) or Red Maple-Larix laricina (Tamarack) swamp. We discuss events that may have led to the current distribution of Bog Turtle populations in central and northern New York and in western Pennsylvania and implications of this distribution pattern for the conservation of the species.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.923
Threshold uncertainty score0.999

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.206
Teacher spread0.192 · 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 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

Citations5
Published2010
Admission routes1
Has abstractyes

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