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Record W4251328647 · doi:10.1346/cms-wls-21-12

On the Use and Abuse of N 2Physisorption for the Characterization of the Pore Structure of Shales

2016· book-chapter· en· W4251328647 on OpenAlexaff
Pieter Bertier, Kevin Schweinar, Helge Stanjek, Amin Ghanizadeh, Christopher R. Clarkson, Andreas Busch, Niko Kampman, Dirk Prinz, Alexandra Amann‐Hildenbrand, Bernhard M. Krooß, Vitaliy Pipich

Bibliographic record

VenueClay Minerals Society eBooks · 2016
Typebook-chapter
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsGeoscience BCUniversity of Calgary
Fundersnot available
KeywordsPhysisorptionCharacterization (materials science)Oil shaleMaterials scienceGeologyChemical engineeringNanotechnologyChemistryEngineeringPhysical chemistryPaleontologyAdsorption

Abstract

fetched live from OpenAlex

Abstract The use of N 2physisorption for the characterization of the pore structure of shales is assessed by addressing some common pitfalls and misconceptions related to the interpretation of physisorption data. In addition, N 2physisorption is compared to other methods used to characterize shales. For this purpose a set of pore-structure and total-porosity data from N 2physisorption, He-pycnometry, Hg-intrusion porosimetry, fluid saturation (Archimedes) methods, and (ultra) small-angle neutron scattering was obtained from measurements on samples of Opalinus Clay.

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 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 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 score0.251
Threshold uncertainty score0.337

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.026
GPT teacher head0.206
Teacher spread0.180 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations12
Published2016
Admission routes1
Has abstractyes

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