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Record W2150684009 · doi:10.1111/wej.12016

Quality assessment of water receiving effluents from crude oil flow stations in <scp>N</scp>iger <scp>D</scp>elta, <scp>N</scp>igeria

2012· article· en· W2150684009 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueWater and Environment Journal · 2012
Typearticle
Languageen
FieldEngineering
TopicWater resources management and optimization
Canadian institutionsnot available
Fundersnot available
KeywordsEffluentWater qualityEnvironmental scienceChemical oxygen demandCrude oilEnvironmental engineeringEngineeringBiologyEcologyWastewaterPetroleum engineering

Abstract

fetched live from OpenAlex

Abstract Waterbodies receiving effluent from six crude oil flow stations in the N iger D elta area of N igeria were assessed. A total of six hundred and forty‐five observations for 19 parameters were used to assess the quality of these waters using the Canadian water quality index. A high correlation was obtained between copper and ammonia ( R = 0.9996, P &lt; 0.01) on one hand, and dissolved oxygen and BOD ( R = 0.786, P &lt; 0.01) on the other. Of the six stations, only one can be classified to be in good conditon, two were in fair conditions, two were marginal, while one was of poor quality. The quality of waterbodies assessed depends more on the degree of violation of standards and the number of times standards were violated. Furthermore, the quality of these waterbodies are affected more by the hydroglogy and geology of the N iger D elta than any other factor.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.508
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.224
Teacher spread0.209 · 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