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Record W332457141

Time Trends for Water Levels in Lake Athabasca, Canada

2012· preprint· en· W332457141 on OpenAlexaboutno aff
Sierra Rayne, Kaya Forest

Bibliographic record

VenueviXra · 2012
Typepreprint
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceHydrology (agriculture)Water levelPhysical geographyClimate changeSeries (stratigraphy)GeologyGeographyOceanography
DOInot available

Abstract

fetched live from OpenAlex

Potential time trends for water levels in Lake Athabasca, Canada, were investigated with particular emphasis on a critical examination of the available hydrometric record and other confounding factors mitigating against reliable trend detection on this sytem. Four hydrometric stations are available on Lake Athbasca, but only the Lake Athabasca near Crackingstone Point (07MC003) site has suitable - albeit temporally limited (1960-2010) - records for a rigorous time series analysis of annual water levels. The examination presented herein provides evidence that the 2010 lake level dataset at 07MC003 is flawed and should not be included in any trend analyses. With the conclusion that 2010 lake levels on Lake Athabasca at station 07MC003 are erroneous, lake level time series regressions over various timeframes between 1960 and 2009 yield widely varying degrees of non-significance and slope magnitude / direction. As a further confounding factor against mechanistic time trend analyses of water levels on Lake Athabasca, a dam and rockfill weirs were constructed on the lake outlets during the 1970s in order to maintain elevated lake levels. Thus, the entire time series of lake levels on Lake Athabasca since filling of the reservoir behind the W.A.C. Bennett Dam (Lake Williston) began in 1968 can be described as experiencing substantial anthropogenic modification. Collectively, these influences - including problems in the hydrometric record - appear to sufficiently impact the annual lake level record as to prevent reliable trend analyses that unequivocally isolate natural factors such as climate change or any other anthropogenic factors that may be operative in the source watersheds.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.694
Threshold uncertainty score0.994

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.017
GPT teacher head0.223
Teacher spread0.206 · 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 designNot applicable
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

Citations0
Published2012
Admission routes1
Has abstractyes

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