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Record W6944320999 · doi:10.17632/5kssw6zvzx

Off-channel aquatic habitat use by river otters and other vertebrates in the Central Platte River Valley, NE

2024· dataset· en· W6944320999 on OpenAlexaboutno aff

Bibliographic record

VenueMendeley Data · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsHabitatOtterHeronWetlandRange (aeronautics)Home rangeBeaverWoodlandWildlife

Abstract

fetched live from OpenAlex

We employed a multi-camera non-linear array sampling design to understand river otter habitat-use patterns in natural and artificial off-channel wetlands along the Platte River. We surveyed 10 off-channel aquatic habitats between 13 February to 15 October 2019. The sites were comprised of 5 pond and 5 slough sites. Each site consisted of a 100-130-meter non-linear array of 3 camera traps placed on existing wildlife trails along the banks of an off-channel aquatic habitat. Individual cameras were spaced between 40 and 75 meters apart within each array, depending upon conditions (availability of animal trails and appropriate topography). Habitat variables were collected at two spatial scales including the macrosite (broader aquatic environment; n = 10) and the microsite (trail along terrestrial-aquatic boundary; n = 30). In addition to documenting river otter occurrences, we recorded all identifiable vertebrate species from camera trap surveys. Therefore, this database has habitat modeling value for a range of other species including mammals such as the American Mink (Neovison vison), American Beaver (Castor canadensis), and Muskrat (Ondatra zibethicus) as well as birds such as the Great Blue Heron (Ardea herodias) or Canada goose (Branta canadensis). Some habitat variables are congruent across spatial scales and others differ. Macrosite habitat variables included maximum and average water depth (m), total water surface area (ac), water pH, water total hardness, mean distance to the river (m), mean distance to dirt road (m), mean distance to paved road (m), mean distance highway (m), mean distance to building (m), mean distance to woodland (m), mean vegetation cover across multiple height classes, the proportional cover of graminoids, forbs, woody species, and groundcover as litter. Microsite variables included all the same distance and vegetation cover metrics but also included bank slope, bank height (m), and control variables like the trail camera height and distance of the camera to the trail. The wetland depth profile was not considered at the microsite level as it reflected features of the larger waterbody. We included river otter scat detection as a validation technique for our river otter relative use metrics which included river otter presence/absence, total river otter captures per camera month, river otter young presence/absence, and river otter young captures per camera month.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.016
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0040.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.017

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 head0.051
GPT teacher head0.280
Teacher spread0.229 · 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
GenreDataset

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
Published2024
Admission routes1
Has abstractyes

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