MétaCan
Menu
Back to cohort
Record W106855906 · doi:10.5006/c2001-01028

Batch Inhibitor Film Distribution Studies: Correlation of Field Data with Laboratory Results

2001· article· en· W106855906 on OpenAlexaff
Josef Bojes, M. Simon Maddison, Harley Fear, Magdy Girgis

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsShell (Canada)Nalco (Canada)Alberta Energy
Fundersnot available
KeywordsMaterials scienceDistribution (mathematics)Field (mathematics)MathematicsMathematical analysis

Abstract

fetched live from OpenAlex

Abstract Batch corrosion inhibitors are extensively used to provide corrosion protection for oil and gas wells as well as the pipelines that transport the hydrocarbons to the processing facilities. The traditional method to estimate the volume of corrosion inhibitor is based on a Rule of Thumb calculation that utilizes a desired film thickness and the length and internal diameter of the pipe to be treated. A discussion of the field and laboratory tests that were conducted to evaluate the thickness of batch inhibitor films and some of the variables that may affect film thickness (e.g. dilution, pig type, production fluids) is presented in this paper.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.022
GPT teacher head0.282
Teacher spread0.260 · 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 source (direct Gemma or distilled Codex), 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

Citations10
Published2001
Admission routes1
Has abstractyes

Explore more

Same topicPetroleum Processing and AnalysisFrench-language works237,207