MétaCan
Menu
Back to cohort
Record W1966245071 · doi:10.1080/10916460701287524

Problems Associated with Conventional Natural Gas Processing and Some Innovative Solutions

2008· article· en· W1966245071 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePetroleum Science and Technology · 2008
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsNatural gasNatural-gas processingMethaneIndustrial gasChemistryRefining (metallurgy)Substitute natural gasHydrogenAdsorptionCarbon dioxideNitrogenWaste managementEnvironmental chemistryChemical engineeringEnvironmental scienceOrganic chemistrySyngasEngineering

Abstract

fetched live from OpenAlex

Abstract On the way from well to the final user, natural gas is treated for various purposes. A typical natural gas stream is a mixture of methane and other hydrocarbons, water vapor, oil and condensates, hydrogen sulfides, carbon dioxide, nitrogen, some other gases, and solid particles. Synthetic chemicals such as glycols, amines, synthetic membranes, and some other adsorbents are used for removing these impurities from the natural gas. In this article, various gas processing methods and toxic chemicals used for gas refining are reviewed. Pathways of these chemicals used in gas processing along with their impacts to humans and the environment are presented. Some prospective natural materials for natural gas processing are also proposed.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.479
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.003
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 head0.011
GPT teacher head0.197
Teacher spread0.186 · 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