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Record W2068861615 · doi:10.2166/wst.2006.320

Development and implementation of a watershed management plan for Lac la Biche, Alberta, Canada

2006· article· en· W2068861615 on OpenAlexaffabout
Jerry White, M. Rawles

Bibliographic record

VenueWater Science & Technology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsLakeland College
Fundersnot available
KeywordsWatershedRiparian zoneRecreationEnvironmental planningWatershed managementWater qualityWater resource managementGeographyEnvironmental resource managementEnvironmental scienceBusinessEnvironmental protectionPolitical scienceEcology

Abstract

fetched live from OpenAlex

Lakeland County is experiencing increasing developmental pressures arising from the oil and gas boom at nearby Fort McMurray. There is increased industrial traffic passing through the county, and 600 new residential lots are proposed in 2005, almost double from 5 years ago. Deteriorating surface water quality has been a concern in the area due to an increase in development and agriculture, while excessive fish harvesting and winterkills have impacted commercial and recreational fisheries. Today, walleye and pike populations in the lake remain collapsed and restocking efforts have not been successful. Due to the lack of studies done on the watershed, the county is leading a multidisciplinary research study which includes a baseline water quality study, riparian health assessments, land use mapping and ground-truthing and projects with the local health authority. This research has been summarized in a comprehensive state of the watershed report, which will be used to complete a watershed management plan for the Lac la Biche watershed. Recommendations from the state of the watershed report and watershed management plan will also be incorporated into municipal planning documents and recommend changes to the Municipal Government Act itself.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.876
Threshold uncertainty score0.859

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 head0.004
GPT teacher head0.197
Teacher spread0.193 · 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

Citations3
Published2006
Admission routes2
Has abstractyes

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