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Record W2519705730 · doi:10.32396/usurj.v2i2.122

Why big cats are at high risk of extinction due to their exceptional predatory abilities. What conservation strategies are needed?

2016· article· en· W2519705730 on OpenAlexaffvenue
Megan D Bjordal

Bibliographic record

VenueUSURJ University of Saskatchewan Undergraduate Research Journal · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsThreatened speciesPredationExtinction (optical mineralogy)BiologyCATSPredatorPopulationEcologyApex predatorHabitatMedicine

Abstract

fetched live from OpenAlex

Cats have highly specialized physical adaptations for hypercarnivory, placing them among the most feared predators. Unique adaptations include strong skulls, sharp teeth, agile and muscular limbs, a taste only for meat, and hyper-retractable claws. These predator adaptations, which characterize the family Felidae, put Felids at high risk of human conflicts. Nearly all of the big cats have threatened or near threatened conservation statuses and 29 of the 37 Felidae species have decreasing population trends. Conservation strategies that consider the large habitats and herbivores required for these specialized predators are needed.

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)0.002
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 score0.113
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.235
Teacher spread0.207 · 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

Citations6
Published2016
Admission routes2
Has abstractyes

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Same venueUSURJ University of Saskatchewan Undergraduate Research JournalSame topicWildlife Ecology and ConservationFrench-language works237,207