MétaCan
Menu
← Back to cohort
Record W6969536037 · doi:10.5683/sp3/7mh2am

Population Survey Data for Coastal Giant Salamanders in the Chilliwack River Valley

2024· dataset· en· W6969536037 on OpenAlexaffabout

Bibliographic record

VenueBorealis · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsThreatened speciesHabitatRiparian zonePopulationHabitat destructionSTREAMSCoastal erosionLand coverLand use

Abstract

fetched live from OpenAlex

The Coastal Giant Salamander (Dicamptodon tenebrosus, formerly known as Pacific giant salamander) is considered a species at risk (Assessed as Threatened by COSEWIC and red-listed by BC-CDC), and the primary putative threat in BC is forestry. Forestry operations impact both the aquatic and terrestrial habitats of the salamanders. Lack of forest cover exposes the adults to wider temperature extremes and the possibility of desiccation. Development of land for farming and settlement along Vedder Mountain and the Cultus Lake area has encroached on the B.C. distribution range of Dicamptodon tenebrosus. Adults depend on riparian forests, which are often removed by logging. In the streams, larvae (and neotenic adults) must cope with more variable stream flows, erosion and sedimentation of stream habitats, and increased water temperatures. This long-term (1994-2001) mark-recapture study of Coastal Giant Salamanders led by Dr. John Richardson (UBC) and Dr. William Neill (UBC) took place in 12 small streams in the Chilliwack River Valley, BC. This study includes survey data to assess whether forest harvest history near the streams or other geomorphic characteristics impacted density, survival, and growth rates. These data, the only long-term data using mark-recapture designs (CJS, using Lebreton design) for this species anywhere, will play a crucial role in future recovery efforts for this threatened species in Canada. The scientific value is high in understanding population dynamics and in the face of continued land use impacts and climate change, offering hope for the future of these salamanders.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.653
Threshold uncertainty score0.690

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.081
GPT teacher head0.333
Teacher spread0.252 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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 routes2
Has abstractyes

Explore more

Same venueBorealis→French-language works237,207→