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Record W2465531551 · doi:10.1186/s40068-016-0070-5

Monitoring and modeling the dispersion of produced water on the Scotian Shelf

2016· article· en· W2465531551 on OpenAlex
Haibo Niu, Kenneth Lee, Brian Robinson, Susan E. Cobanli, Pu Li

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueENVIRONMENTAL SYSTEMS RESEARCH · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicOil Spill Detection and Mitigation
Canadian institutionsBedford Institute of OceanographyFisheries and Oceans CanadaDalhousie University
FundersEnvironmental Studies Research FundsEuropean Synchrotron Radiation Facility
KeywordsPlumeEnvironmental scienceDilutionPollutantSubmarine pipelineDispersion (optics)Sampling (signal processing)Hydrology (agriculture)SeawaterOceanographyMeteorologyGeologyChemistryEngineeringGeotechnical engineering

Abstract

fetched live from OpenAlex

Produced water from offshore oil and gas platforms is often disposed of directly into the sea, and there has been concern that this discharge might have deleterious effects on the marine environment. To help understand the patterns of dispersion and dilution of produced water discharges, and their potential effects, a combined modeling and monitoring study was conducted. Chemical analysis of representative produced water samples recovered from the Sable Offshore Energy Project (SOEP) Venture platform showed elevated concentrations of several organic and inorganic compounds of environmental concern; however, of the 25 stations sampled within 500 m of the platform, only one station, NE50, located 50 m to the northeast, showed chemicals associated with produced water at levels significantly above background values. The Dose-related Risk and Effect Assessment Model (DREAM) was used to evaluate the fate and transport processes of produced water after discharge. The results revealed that the near background level concentrations detected at the 26 stations were due to sampling outside the narrow plume boundary. This indicated that there was no accumulation of pollutants near the platform except inside the narrow plume. The comparison of modeled and empirical data showed that the DREAM model can effectively predict plume behaviour. The results agreed well with the monitoring data and simulated the location of the plume as it changed continuously with the tidal currents. The model illustrated that elevated concentrations within the produced water plume occur only near the vicinity of the discharge.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.673

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)0.0000.001

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 head0.048
GPT teacher head0.277
Teacher spread0.229 · 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