MétaCan
Menu
Back to cohort
Record W2077015565 · doi:10.14796/jwmm.c383

Assessing the Impacts of Stormwater Runoff from I-59 to a Headwater Stream in Central Alabama

2014· article· en· W2077015565 on OpenAlex
Mitchell F. Moore, Catherine G. Butler, José G. Vasconcelos

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Water Management Modeling · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Resources Studies
Canadian institutionsnot available
FundersAlabama Department of TransportationU.S. Department of Transportation
KeywordsStormwaterSurface runoffEnvironmental scienceStormwater managementHydrology (agriculture)Aquatic ecosystemSTREAMSWater resource managementGeologyEcologyGeotechnical engineeringComputer scienceOceanography

Abstract

fetched live from OpenAlex

Some studies have shown that stormwater runoff may have constituents that cause adverse impacts to aquatic ecosystems. Various related studies have focused either on characterizing the runoff directly generated on roads or on the effectiveness of various pollutant removal techniques. This work presents and discusses the results of an ongoing investigation on the impact of stormwater runoff from an interstate highway measured at a receiving stream. Water samples were collected at selected points and hydrological and water quality parameters were continuously monitored in selected stations. Quality parameters included nitrogen and phosphorus species, dissolved oxygen, total suspended solids and total solids, pH, turbidity, specific conductivity and temperature. Ongoing work attempts to establish a relationship between highway traffic, time between rain events, rainfall depth and changes in water quality parameters in the stream as a result of road runoff. The purpose of this study is to quantify and assess road impacts on a small Alabama watershed and how it differs from impacts caused by other land uses in watersheds, and whether traffic and the proximity of an interstate highway are related to such impacts.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.433
Threshold uncertainty score0.312

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 science0.0000.000
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 head0.038
GPT teacher head0.260
Teacher spread0.223 · 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