MétaCan
Menu
Back to cohort
Record W4403375156 · doi:10.1080/11956860.2024.2404796

Has river regulation damaged the Peace-Athabasca Delta?

2024· article· fr· W4403375156 on OpenAlexfundvenueno aff
Kevin P. Timoney

Bibliographic record

VenueEcoscience · 2024
Typearticle
Languagefr
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersBC Hydro
KeywordsDeltaEcologyGeographyEnvironmental scienceBiologyEngineering

Abstract

fetched live from OpenAlex

The Peace-Athabasca Delta (PAD) is a complex, dynamic, and misunderstood ecosystem. This study uses landscape, ecological, climatic, hydrologic, historical, stratigraphic, and wildlife data that document how and why the PAD has changed and varied from ~1900 to 2023. The ecological, climatic, and hydrologic components of the ecosystem vary in concert. Flood-drawdown cycles influenced by physical and biological factors have driven a host of landscape changes over the past 120 years. Prior to regulation, net drying of the PAD took place over the period ~1900 to the mid-1940s. Since mid-20th century, there has been no multidecadal drying trend but rather decadal-scale wet and dry episodes. Levels of the confluent Lakes Athabasca, Claire, and Mamawi, and their adjacent restricted basins, are strongly correlated with the combined flows of the Peace, Athabasca, Fond du Lac, and Birch Rivers. River regulation has changed the seasonal distribution of flows and suppressed summer flows. There is, however, no evidence that ‘dramatic landscape change is underway, devastating local fauna’ or that river regulation has caused delta desiccation, declines in spring flooding, declines in lake levels, or declines in wildlife, waterfowl, or their habitat. The great areal extent of the PAD watershed imparts hydrologic and ecological resilience.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.898
Threshold uncertainty score0.203

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.227
Teacher spread0.209 · 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

Citations2
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueEcoscienceSame topicFish Ecology and Management StudiesFrench-language works237,207