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Record W2171898463 · doi:10.2744/ccb-0847.1

The Complex Linear Home Range Estimator: Representing the Home Range of River Turtles Moving in Multiple Channels

2011· article· en· W2171898463 on OpenAlexaffabout
Mathieu Ouellette, Jeffrey A. Cardille

Bibliographic record

VenueChelonian Conservation and Biology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicTurtle Biology and Conservation
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHome rangeEstimatorRange (aeronautics)Polygon (computer graphics)Turtle (robot)BiologyFisheryHabitatComputer scienceEcologyStatisticsMathematicsTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

We studied the home range and habitat use of northern map turtles (Graptemys geographica) in Québec, Canada, in a river comprised of multiple channels and islands. To better represent the home range of turtles in such complex river landscapes, we developed the complex linear home range (CLHR), a generalized estimator designed to more accurately represent turtle home ranges based on their movements in multiple channels, unlike the simple well-known linear home range and the minimum convex polygon estimators. The CLHR appears to be an estimator that can permit the interstudy comparison of turtle home ranges in other rivers characterized by multiple channels and can be calculated easily using GIS software.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.355

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 studies0.0000.001
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 head0.082
GPT teacher head0.261
Teacher spread0.179 · 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

Citations13
Published2011
Admission routes2
Has abstractyes

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