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Record W2731067974 · doi:10.15760/honors.461

Emerging Pollutants in the Columbia River: A Simple Assessment of Nonpoint Source Zones

2017· dissertation· en· W2731067974 on OpenAlexaboutno aff
Chulgi Kim

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicWater Quality and Resources Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHydrology (agriculture)WatershedEnvironmental scienceSurface runoffDrainage basinNonpoint source pollutionWater qualityPollutantDischargeMileGeographyGeologyEcologyCartography

Abstract

fetched live from OpenAlex

Water quality modeling in the Columbia River Basin was conducted at the confluence of the Willamette and Columbia Rivers, river mile 101. The study area for this research consists of Sauvie Island, OR, and the surrounding areas of Vancouver, WA. Analysis of the region’s watershed and simple hydrologic calculations allowed for estimates of potential sources contributing to PBDEs in the Columbia River along river mile 101. This research included assessment of rainfall patterns and peak discharge rates in the areas along the rivers. A simple model of overland flow for the watershed was applied to estimate the area’s contribution to overall flow in the Columbia River. Potential impacts and possible sources for emerging pollutants in the Columbia River at river mile 101 were inferred from this analysis.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.302
Teacher spread0.272 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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