MétaCan
Menu
Back to cohort
Record W3120008170 · doi:10.1002/hyp.14038

The Baker Creek Research Watershed: Streamflow data highlighting the behaviour of an intermittent Canadian Shield stream through a wet–dry–wet cycle

2021· article· en· W3120008170 on OpenAlexafffundabout
Christopher Spence, N. Hedstrom

Bibliographic record

VenueHydrological Processes · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsEnvironment and Climate Change Canada
FundersGlobal Water FuturesNatural Sciences and Engineering Research Council of CanadaEnvironment and Climate Change CanadaGarfield Weston FoundationPolar Knowledge Canada
KeywordsBedrockHydrology (agriculture)StreamflowWatershedDrainage basinCatchment hydrologyPermafrostSubarctic climateSTREAMSEnvironmental scienceGeologyGeomorphologyGeographyOceanography

Abstract

fetched live from OpenAlex

Abstract Baker Creek drains water from subarctic Canadian Shield terrain comprised of a mix of exposed Precambrian bedrock, lakes, open black spruce forest and peat filled depressions. Research in the catchment has focused on hydrological processes at the hillslope and catchment scales. Streamflow is gauged from several diverse sub‐catchments ranging in size from 9 to 155 km 2 . The period of record (2003–2019) of streamflow from these sub‐catchments extends from 12 to 17 years, and these data are the focus of this note. Such data are unique in this remote region. 2003–2019 was a period that included both historic wet and dry conditions. Observations during such a diversity of conditions are helping to improve understanding of how stream networks that drain this landscape expand and contract in response to short and long hydroclimatic cycles. These data from a distinctly cold and dry region of low relief, thin soils, exposed bedrock and permafrost are a valuable contribution to the global diversity of research catchment data.

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 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 score0.636
Threshold uncertainty score0.997

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.151
GPT teacher head0.330
Teacher spread0.179 · 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

Citations5
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueHydrological ProcessesSame topicClimate change and permafrostFrench-language works237,207