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Record W3165550840 · doi:10.1029/2021jb022228

Magnetic and Gravity Surface Geometry Inverse Modeling of the TAG Active Mound

2021· article· en· W3165550840 on OpenAlexafffund
Christopher Galley, Peter G. Lelièvre, Amir Haroon, S. David Graber, John W. Jamieson, Florent Szitkar, Isobel Yeo, Colin G. Farquharson, Sven Petersen, R. L. Evans

Bibliographic record

VenueJournal of Geophysical Research Solid Earth · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsMount Allison UniversityMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaMemorial University of NewfoundlandNatural Environment Research CouncilSight Research UK
KeywordsGeologySeafloor spreadingRidgeHydrothermal circulationMagnetic anomalyBasaltGeophysicsDrillingVolcanogenic massive sulfide ore depositGeochemistrySeismologyPaleontology

Abstract

fetched live from OpenAlex

Abstract Seafloor massive sulfide deposits form in remote environments, and the assessment of deposit size and composition through drilling is technically challenging and expensive. To aid the evaluation of the resource potential of seafloor massive sulfide deposits, three‐dimensional inverse modeling of geophysical potential field data (magnetic and gravity) collected near the seafloor can be carried out to further enhance geologic models interpolated from sparse drilling. Here, we present inverse modeling results of magnetic and gravity data collected from the active mound at the Trans‐Atlantic Geotraverse hydrothermal vent field, located at 26 ° 08′N on the Mid‐Atlantic Ridge, using autonomous underwater vehicle and submersible surveying. Both minimum‐structure and surface geometry inverse modeling methods were utilized. Through deposit‐scale magnetic modeling, the outer extent of a chloritized alteration zone within the basalt host rock below the mound was resolved, providing an indication of the angle of the rising hydrothermal fluid and the depth and volume of seawater/hydrothermal mixing zone. The thickness of the massive sulfide mound was determined by modeling the gravity data, enabling the tonnage of the mound to be estimated at 2.17 ± 0.44 Mt through this geophysics‐based, noninvasive approach.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.784
Threshold uncertainty score0.511

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.049
GPT teacher head0.328
Teacher spread0.278 · 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 designOther design
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

Citations22
Published2021
Admission routes2
Has abstractyes

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