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Record W6947955656 · doi:10.48433/cr_msm103

Groundwater Resources Offshore Prince Edward Island, Canada, Cruise No. MSM103, 12.9. - 15.11.2021, Emden (Germany) - Halifax (Canada) - Emden (Germany)

2022· report· en· W6947955656 on OpenAlexaboutno aff

Bibliographic record

VenueHelmholtz Centre for Ocean Research Kiel (GEOMAR) · 2022
Typereport
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsCruiseSubmarine pipelineAquiferSeabedSedimentSeafloor spreadingGroundwaterChannel (broadcasting)

Abstract

fetched live from OpenAlex

During cruise MSM103 (12.9. 15.11.2021), carried out as part of the SOURCE project, multidisci-plinary investigations were carried out in the Gulf of St. Lawrence Gulf north of Prince EdwardIsland (PEI) to identify and quantify offshore aquifers in the region. For this purpose, seismic, elec-tromagnetic and hydroacoustic measurements were carried out and sediment samples were obtainedwith the gravity corer. The structure of the seabed and the seafloor were explored using acousticmethods. A large number of channel structures could be detected in sections, which are interpretedas parts of glacial or postglacial drainage systems. It is not yet possible to say whether these are con-nected to any existing deeper groundwater systems. In the hydroacoustic data, no escapes of freshwater or gas could be observed in the water column during the cruise. In several places, however, ablanking was evident in the seafloor, which indicates the occurrence of gases and could hint atpotential pathways for gas and / or freshwater in the seafloor. Here, an extended evaluation of thehydroacoustic data after the cruise will provide further insight. In sediment samples taken at a loca-tion north of PEI, a significant drop in salinity and resistivity could be detected in the upper 3m ofthe sediment, which provided a first direct indication of the presence of fresher groundwater. Fromthe electromagnetic measurements carried out in seven working areas, we hope to be able to con-tinue this punctual information over larger areas in order to obtain an extended insight into the pres-ence and distribution of freshwater deposits by the detection of anomalies of the electricalconductivity.

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)0.000
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 score0.043
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.002

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 head0.019
GPT teacher head0.294
Teacher spread0.276 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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