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Record W3210326587 · doi:10.1038/s43247-021-00297-2

Geothermal heating and episodic cold-seawater intrusions into an isolated ridge-flank basin near the Mid-Atlantic Ridge

2021· article· en· W3210326587 on OpenAlexaff
Keir Becker, Richard E. Thomson, Earl E. Davis, Heinrich Villinger, C.G. Wheat

Bibliographic record

VenueCommunications Earth & Environment · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsGeological Survey of CanadaNatural Resources CanadaFisheries and Oceans Canada
FundersDeutsche ForschungsgemeinschaftUniversity of Southern CaliforniaGordon and Betty Moore FoundationNational Science Foundation
KeywordsGeologyBottom waterRidgeStructural basinSillWater massGeothermal gradientOceanographyAntarctic Bottom WaterSeawaterGeochemistryGeomorphologyPaleontology

Abstract

fetched live from OpenAlex

Abstract Six-year records of ocean bottom water temperatures at two locations in an isolated, sedimented deep-water (∼4500 m) basin on the western flank of the mid-Atlantic Ridge reveal long periods (months to >1 year) of slow temperature rises punctuated by more rapid (∼1 month) cooling events. The temperature rises are consistent with a combination of gradual heating by the geothermal flux through the basin and by diapycnal mixing, while the sharper cooling events indicate displacement of heated bottom waters by incursions of cold, dense bottom water over the deepest part of the sill bounding the basin. Profiles of bottom water temperature, salinity, and oxygen content collected just before and after a cooling event show a distinct change in the water mass suggestive of an incursion of diluted Antarctic Bottom Water from the west. Our results reveal details of a mechanism for the transfer of geothermal heat and bottom water renewal that may be common on mid-ocean ridge flanks.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.022
GPT teacher head0.242
Teacher spread0.220 · 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; both teacher heads agree on what is shown here.

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

Citations2
Published2021
Admission routes1
Has abstractyes

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