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Development of a New Method of Extraction of Interstitial Water from Low‐Porosity Consolidated Sediments Recovered During Super‐Deep Drilling Projects

2015· article· en· W1806691698 on OpenAlexaff
Tomohiro Toki, Harue Masuda, Harunur Rashid, Sebastian Hammerschmidt, Ryuichi Shinjo

Bibliographic record

VenueGeostandards and Geoanalytical Research · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsMemorial University of Newfoundland
FundersJapan Agency for Marine-Earth Science and Technology
KeywordsGrindUltrapure waterPorosityExtraction (chemistry)DrillingGeologySedimentGroundwaterMineralogyEnvironmental scienceMaterials scienceGeotechnical engineeringMetallurgyChemistryGeomorphologyEnvironmental engineeringChromatography

Abstract

fetched live from OpenAlex

During the Integrated Ocean Drilling Program ( IODP ) Expedition 338, several methods were tested for the extraction of interstitial water in consolidated, low‐porosity deep‐sea sediments from Site C0002 in the Kumano Basin. On the basis of those tests, we propose a modified ground rock interstitial normative determination ( GRIND ) method of extraction of interstitial water. In separate runs of the new method, sediment samples were ground in a ball mill with either ultrapure water or a solution of HNO 3 . The interstitial water was then extracted with a conventional squeezer. Sufficient solution was extracted by this method to analyse most major and a few minor components of interstitial water that were comparable to those previously reported for samples extracted by the conventional squeezing method. The new method requires much smaller amounts of sediment than that of the conventional method and will be useful for analysis of samples recovered during super‐deep drilling programmes.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.041
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0010.000

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 head0.069
GPT teacher head0.374
Teacher spread0.304 · 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.

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

Citations1
Published2015
Admission routes1
Has abstractyes

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