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Record W2287876505 · doi:10.1139/cjes-2015-0228

Earth evolution and dynamics—a tribute to Kevin Burke

2016· article· en· W2287876505 on OpenAlexvenueno aff
Trond H. Torsvik, Bernhard Steinberger, Lewis D. Ashwal, Pavel V. Doubrovine, Reidar G. Trønnes

Bibliographic record

VenueCanadian Journal of Earth Sciences · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyMantle (geology)Plate tectonicsMantle convectionMantle plumeHotspot (geology)LithosphereSubductionKimberliteGeophysicsTectonophysicsTectonicsPaleontology

Abstract

fetched live from OpenAlex

Kevin Burke’s original and thought-provoking contributions have been published steadily for the past 60 years, and more than a decade ago he set out to resolve how plate tectonics and mantle plumes interact by proposing a simple conceptual model, which we will refer to as the Burkian Earth. On the Burkian Earth, mantle plumes take us from the deepest mantle to sub-lithospheric depths, where partial melting occurs, and to the surface, where hotspot lavas erupt today, and where large igneous provinces and kimberlites have erupted episodically in the past. The arrival of a plume head contributes to continental break-up and punctuates plate tectonics by creating and modifying plate boundaries. Conversely, plate tectonics makes an essential contribution to the mantle through subduction. Slabs restore mass to the lowermost mantle and are the triggering mechanism for plumes that rise from the margins of the two large-scale low shear-wave velocity structures in the lowermost mantle, which Burke christened TUZO and JASON. Situated just above the core–mantle boundary, beneath Africa and the Pacific, these are stable and antipodal thermochemical piles, which Burke reasons represent the immediate after-effect of the moon-forming event and the final magma ocean crystallization.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.405
Threshold uncertainty score0.991

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.192
Teacher spread0.182 · 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 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

Citations93
Published2016
Admission routes1
Has abstractyes

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