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Ancient slabs beneath Arctic and surroundings: Izanagi, Farallon, and in-betweens

2024· other· en· W6977472057 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2024
Typeother
Languageen
FieldEarth and Planetary Sciences
TopicMeteorological Phenomena and Simulations
Canadian institutionsnot available
Fundersnot available
KeywordsSubductionSlab windowSlabMantle (geology)Mantle wedgeTransition zoneMid-ocean ridge

Abstract

fetched live from OpenAlex

Abstract A detailed 3-D tomographic model of the whole mantle beneath the northern hemisphere (north of ~ 30°N latitude) is obtained by inverting a large amount of P-wave arrival time data (P, pP, and PP) to investigate transition of subducted slabs beneath Eurasia–Arctic–North America. We apply an updated global tomographic method that can investigate the whole mantle 3-D structure beneath a target area with high resolution comparable to that of regional tomography. The final tomographic model is obtained by performing independent calculations for 12 different target areas and stitching together the results. Our model clearly shows the subducted Izanagi and Farallon slabs penetrating into the lower mantle beneath Eurasia and North America, respectively. In the region from Canada to Greenland, a stagnant slab lying below the 660-km discontinuity is revealed. Because this slab has a texture that seems to be due to subducted oceanic ridges, the slab might be composed of the Farallon and Kula slabs that had subducted during ~60–50 Ma. During that period, a complex rift system represented by division between Canada and Greenland was developed. The oceanic ridge subduction and hot upwelling in the big mantle wedge above the stagnant slab caused a tensional stress field, which might have induced these complex tectonic events.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.188
Threshold uncertainty score0.374

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.038
GPT teacher head0.240
Teacher spread0.202 · 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 designSimulation or modeling
Domainnot available
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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