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Record W2930160681 · doi:10.12789/geocanj.2019.46.145

An Overview of the Karst Areas in British Columbia, Canada

2019· article· en· W2930160681 on OpenAlexaffvenueabout
Tim Stokes, Paul A. Griffiths

Bibliographic record

VenueGeoscience Canada · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicKarst Systems and Hydrogeology
Canadian institutionsVancouver Island University
Fundersnot available
KeywordsKarstCaveGeologySinkholeBedrockGeomorphologyHydrology (agriculture)ArchaeologyGeographyPaleontology

Abstract

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Karst is a three-dimensional landscape that occurs in soluble bedrock (typically limestone, marble, dolostone, gypsum or halite) and is defined by a solutionally weathered surface, a subsurface drainage system (where conduit-flow dominates), and underground openings and caves. Karst can host unique flora and subsurface fauna, as well as a wide range of other scientific, recreational and cultural values. Karst and potential karst areas underlie approximately 10% of British Columbia (BC), but the distribution and extent of this landscape has yet to be fully explored and delineated. Some of the most extensive and well-developed karst areas occur within the forestedlimestone areas of coastal BC, such as on Vancouver Island and Haida Gwaii, where numerous surface karst features and caves are known. Karst in the interior plateau regions of British Columbia is less well known, being in part covered by thick deposits of glacial materials. Alpine karst regions are most apparent in the Rocky Mountains where there are limestone plateaus, karst drainages and cave systems that have close connections to past and present glacial systems. Mapping of karst is a critical component for any land-use or resource development activity in all regions of British Columbia, as the environmental impacts on karst and its associated values are potentially significant. The regional distribution of karst in BC is not well mapped, with only an office-based reconnaissance karst potential map (1:250,000-scale) and a related database completed in 1999. A renewed effort should now be made to better map karst across British Columbia using digital bedrock mapping data released in 2017, combined with more recent satellite imagery and improved field knowledge.RÉSUMÉLe karst est un paysage tridimensionnel qui se présente dans le substrat rocheux soluble (généralement calcaire, marbre, dolomite, gypse ou halite) et est défini par une surface altérée par dissolution, un système de drainage souterrain (où l’écoulement par conduit domine) et des ouvertures et cavernes souterraines. Le karst peut abriter une flore et une faune souterraine unique, ainsi qu’une grande variété d’autres ressources scientifiques, de loisir et culturelles. Les zones karstiques et potentiellement karstiques constituent environ 10% de la surface de la Colombie-Britannique, mais la répartition et l’étendue de ce paysage n’a pas été complètement explorées et circonscrites. Certaines des zones karstiques les plus étendues et les mieux développées se trouvent dans les calcaires des zones calcaires boisées de la côte de la Colombie-Britannique, telles que l’île de Vancouver et l’archipel de Haida Gwaii, où l’on connaît de nombreuses caractéristiques karstiques de surface et des cavernes. Le karst des régions des plateaux intérieurs de la Colombie-Britannique est moins bien connu, étant en partie recouvert d’épais dépôts de matériaux glaciaires. Les régions karstiques alpines sont plus apparentes dans les montagnes Rocheuses où se trouvent des plateaux calcaires, des bassins de drainage karstiques et des systèmes de cavernes étroitement liés aux systèmes glaciaires passés et contemporains. La cartographie du karst est une constituante essentielle de toute activité d’utilisation du terrain ou de développement des ressources dans toutes les régions de la Colombie-Britannique, car les impacts environnementaux sur le karst et ses bénéfices associés sont potentiellement importants. La distribution régionale et les caractéristiques des karsts en Colombie-Britannique ne sont pas bien cartographiées, avec seulement une carte de reconnaissance du potentiel karstique établie par une étude de bureau (à l’échelle de 1/250 000) et une base de données associée, complétées en 1999. Il faut aujourd’hui améliorer la cartographie de karsts en Colombie-Britannique en utilisant les données numériques de cartographie du substrat rocheux publiées en 2017, combinées avec des images satellite plus récentes et à une meilleure connaissance du terrain.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.259

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0070.018
Science and technology studies0.0050.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0220.002

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 head0.010
GPT teacher head0.182
Teacher spread0.172 · 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 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

Citations10
Published2019
Admission routes3
Has abstractyes

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