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Record W2129627462 · doi:10.2981/07-093

The Use of an Orthotic Casting Foam as a Track‐Plate Medium for Wildlife Research and Monitoring

2009· article· en· W2129627462 on OpenAlexaff
Justin B. Hooper, Roy V. Rea

Bibliographic record

VenueWildlife Biology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsTrack (disk drive)CastingComputer scienceMaterials scienceMarine engineeringMechanical engineeringComposite materialEngineering

Abstract

fetched live from OpenAlex

Track plates are an inexpensive, non‐intrusive and widely used wildlife monitoring tool. Almost all track‐plate media are not suited for use during rainy conditions, because rain or heavy dews can distort tracks or render the medium ineffective for registering further animal visitations. Furthermore, available track‐plate media may also produce tracks of varying quality and hard‐surfaced media produce inaccurate two‐dimensional imprints. We experimented with the utility of using Biofoam™, a phenolic foam used in orthotics, as a track‐plate medium. Domestic animals were utilized to produce track imprints on track plates constructed of casting foam, coarse sand, fine sand, very fine sand and sooted aluminum. Resulting tracks were photographed and images were used in a questionnaire which was completed by expert wildlife trackers who rated the quality of the tracks. Tracks in the casting foam are three‐dimensional, register claws, clearly depict all pads, accurately record shape and size, and convey very fine anatomical details. Track imprints on the casting foam were rated consistently better by experts than track imprints left on the other media. Field trials demonstrated that the casting foam and tracks in the casting foam can endure lengthy periods of inclement weather conditions in the field without being damaged or distorted. In summary, where three‐dimensional, high‐quality prints need to be recorded in variable field conditions, we recommend the use and further experimentation with track plates made of casting foam.

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)0.001
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 score0.029
Threshold uncertainty score0.455

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.115
GPT teacher head0.348
Teacher spread0.233 · 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

Citations3
Published2009
Admission routes1
Has abstractyes

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