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Record W2299275611 · doi:10.1016/j.ejrh.2016.01.034

Stable isotope mass balance of fifty lakes in central Alberta: Assessing the role of water balance parameters in determining trophic status and lake level

2016· article· en· W2299275611 on OpenAlexafffundabout
J. J. Gibson, S. J. Birks, Yuanbi Yi, Michael C. Moncur, Preston McEachern

Bibliographic record

VenueJournal of Hydrology Regional Studies · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsAlberta InnovatesUniversity of AlbertaUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates
KeywordsEnvironmental scienceEutrophicationHydrology (agriculture)Water balanceTrophic levelGroundwaterEcologyGeologyNutrient

Abstract

fetched live from OpenAlex

Study region: This study spans the Prairie/parkland/boreal transition in central Alberta, including lakes in the Athabasca, North Saskatchewan, Battle River and Red Deer Basins.
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\nStudy focus: Stable isotopes of water, oxygen-18 and deuterium, were measured in a network of 50 lakes during 2008 and 2009. The lakes are the subject of recent concern due to widespread lake level decline and development of eutrophic conditions that have been attributed to climate and land-use impacts. An isotope mass balance method was applied to estimate evaporation/inflow, water yield, and water residence times to assess relationships between water balance and lake status.
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\nNew hydrological insights: Water yield was found to range from near 0 to 235 mm, evaporation/inflow was found to range from 18 to 136 %, and water residence time ranged from 2.3 to 58 years. The healthiest lakes in terms of trophic status are deep lakes with smaller catchments with long residence times. These lakes may have stable or variable water levels. Distressed lakes are often shallow prairie lakes with limited inflow and shorter residence times, and situated in areas with higher evaporation rates. High conductivity and high sulfate in some eutrophic lakes, attributed to saline groundwater inflow, may inhibit algae and cyanobacterial growth, thereby promoting healthier conditions. Extended drought under climate warming is expected to cause eventual decline of water levels in a greater number of lakes.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.003
Threshold uncertainty score0.218

Codex and Gemma teacher scores by category

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

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 head0.025
GPT teacher head0.239
Teacher spread0.214 · 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.

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

Citations68
Published2016
Admission routes3
Has abstractyes

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