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Record W7106264611 · doi:10.1594/pangaea.986841

Magnetic data of profile MSM122_SH18 to the south of Hayes transform fault, North Atlantic, of MARIA S. MERIAN cruise MSM122

2025· dataset· en· W7106264611 on OpenAlexaboutno aff

Bibliographic record

VenueOpen MIND · 2025
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
FundersEuropean Research CouncilDeutsche Forschungsgemeinschaft
KeywordsCruiseMagnetometerEarth's magnetic fieldSternMagnetic surveySampling (signal processing)Position (finance)

Abstract

fetched live from OpenAlex

During the cruise MSM122 of the German research vessel MARIA S. MERIAN, we recorded densely spaced magnetic field measurement over the Oceanographer and Hayes transform faults in the North Atlantic to the Southwest of the Azores and hence at segment boundries offseting the Mid-Atlantic Ridge. Additional data were recorded to the south of Hayes transform and on the transits to Halifax outside of any territorial water.The total magnetic field was measured using two SeaSpy magnetometers which were towed at 350 m and 450 m, respectively, behind the stern of the ship, sampling the data continuously every 2 seconds. The ships navigation was corrected to match the position of the first magnetic sensor at 350 m behind the vessel. Uncorrected total field magnetic data are available in text/ascii format.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.062
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0400.058

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 head0.046
GPT teacher head0.321
Teacher spread0.275 · 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 designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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