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Record W3043358707 · doi:10.1144/sp503-2020-7

Pannotia's mantle signature: the quest for supercontinent identification

2020· article· en· W3043358707 on OpenAlexafffund
Philip J. Heron, J. Brendan Murphy, R. Damian Nance, R. N. Pysklywec

Bibliographic record

VenueGeological Society London Special Publications · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of TorontoSt. Francis Xavier University
FundersH2020 Marie Skłodowska-Curie ActionsUniversity of TorontoCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaGovernment of OntarioNational Science Foundation
KeywordsSupercontinentGeologyIdentification (biology)Mantle (geology)GeophysicsPaleontologyCratonBiologyTectonics

Abstract

fetched live from OpenAlex

Abstract A supercontinent is generally considered to reflect the assembly of all, or most, of the Earth's continental lithosphere. Previous studies have used geological, atmospheric and biogenic ‘geomarkers’ to supplement supercontinent identification. However, there is no formal definition of how much continental material is required to be assembled, or indeed which geomarkers need to be present. Pannotia is a hypothesized landmass that existed in the interval c. 0.65–0.54 Ga and was comprised of Gondwana, Laurentia, Baltica and possibly Siberia. Although Pannotia was considerably smaller than Pangaea (and also fleeting in its existence), the presence of geomarkers in the geological record support its identification as a supercontinent. Using 3D mantle convection models, we simulate the evolution of the mantle in response to the convergence leading to amalgamation of Rodinia and Pangaea. We then compare this supercontinent ‘fingerprint’ to Pannotian activity. For the first time, we show that Pannotian continental convergence could have generated a mantle signature in keeping with that of a simulated supercontinent. As a result, we posit that any formal identification of a supercontinent must take into consideration the thermal evolution of the mantle associated with convergence leading to continental amalgamation, rather than simply the size of the connected continental landmass.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.217
Teacher spread0.193 · 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 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

Citations13
Published2020
Admission routes2
Has abstractyes

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