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Record W2742761926 · doi:10.1594/pangaea.757579

Chemical sensor measurements at the sediment surface of the Håkon Mosby mud volcano (LOOME)

2009· dataset· en· W2742761926 on OpenAlexaboutno aff
Dirk de Beer

Bibliographic record

VenueFigshare · 2009
Typedataset
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsnot available
FundersSixth Framework Programme
KeywordsMud volcanoGeologyVolcanoSedimentGeomorphologyOceanographyGeochemistryHydrology (agriculture)Geotechnical engineering

Abstract

fetched live from OpenAlex

Six sensor units each having a pH, dissolved oxygen (DO) and oxidation reduction potential (ORP) sensor, plus a central logger, and connection cables were purchased from RBR (Ottawa). The sensing loggers were placed at a transect across the hot spot. Unfortunately, 5 of the 7 loggers were drowned. Only the central logger, that collected the data from the 6 sensor loggers, and one of the sensor loggers remained dry and functional. The sensor was positioned at 50 m south of the frame, in the center of the hot spot. The ORP did not show interpretable signals. The DO and pH signals showed good correlation (. At the end of October 2009 both signals decreased, the pH became as low as 4, possibly indicating increased seepage, or burial in expelled sediments. In December both sensors regained seawater values and then decreased again until the end of May 2010. A pH of 4 can only be reached by very high carbondioxide levels. The dynamics of the signals indicate eruptions and sediment movements from October 2009 till the end of the deployment.

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)0.000
metaresearch head score (Gemma)0.001
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.103
Threshold uncertainty score0.205

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.004

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 head0.032
GPT teacher head0.235
Teacher spread0.204 · 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
GenreDataset

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

Citations0
Published2009
Admission routes1
Has abstractyes

Explore more

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