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Record W1997643846 · doi:10.2747/0020-6814.47.6.591

Do Supercontinents Turn Inside-in or Inside-out?

2005· article· en· W1997643846 on OpenAlexfundno aff
J. Brendan Murphy, R. Damian Nance

Bibliographic record

VenueInternational Geology Review · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsSupercontinentGeologyLithosphereSubductionBreakupArcheanPaleontologyMantle (geology)RodiniaPlate tectonicsTerraneGeophysicsEarth scienceTectonicsCraton

Abstract

fetched live from OpenAlex

Abstract Supercontinent amalgamation and dispersal has occurred repeatedly since the Archean. However, the mechanisms responsible for these events are unclear. Following supercontinent breakup, two geodynamically distinct oceans may be distinguished: an interior ocean formed between the dispersing continents, whose lithosphere is younger than the time of supercontinent breakup (TR); and an exterior ocean that surrounded the supercontinent prior to breakup, and consequently is dominated by lithosphere that is older than the time of breakup. In order to evaluate geodynamic models for supercontinent formation, it is essential to determine which of these two types of ocean is consumed during supercontinent amalgamation. Although much of the evidence needed is destroyed by subduction, vestiges of oceanic lithosphere are preserved in mafic complexes accreted to continental margins prior to terminal collision. Because the age contrast between interior and exterior oceans diminishes as the continents drift apart, the ages of the earliest accreted complexes are the most diagnostic of the ocean in which they formed. Constraints on the age of the mantle lithospheric sources (TDM) that give rise to these accreted complexes can be derived from Sm-Nd isotope systematics. In the case of Pangea, for example, the North American Cordillera represents an accretionary orogen along the leading edge of a dispersing supercontinent. Within this orogen, the oldest accreted oceanic terranes, characterized by high εNd values close to contemporary depleted mantle values, show similar crystallization and TDM model ages that imply crustal formation and arc activity during the lifespan of Pangea, that is, within the exterior Panthalassa ocean (i.e., TDM>TR). This example suggests that a similar approach applied to older orogens may constrain the relationship between continental margins and their accreted mafic complexes. Pangea was formed by closure of Paleozoic oceans (e.g., Iapetus and Rheic) that were formed after the ca. 550 Ma breakup of Pannotia. Uncontaminated mafic rocks from both oceans that have εNd values close to depleted mantle values at their respective times of emplacement show closely matching crystallization and depleted mantle model ages that do not exceed the age of rifting (i.e., TDM ≥ TR). This indicates that the oceanic lithospheric source of these suites was generated after the rifting of Pannotia, such that Pangea was formed by the closure of interior oceans (introversion). In contrast, mafic terranes accreted in orogens that terminated in the formation of the Late Neoproterozoic supercontinent Pannotia have Sm-Nd TDM model ages between ca. 1.2 and 0.71 Ga, implying that much of the oceanic lithosphere that was subducted and recycled to yield these complexes was formed before the ca. 755 Ma breakup of the supercontinent Rodinia (i.e. TDM > TR). These mafic complexes are therefore vestiges of oceanic lithosphere that formed within the peri-Rodinian ocean, such that Pannotia was formed by the closure of an exterior ocean (extroversion). This analysis suggests that Pangea and Pannotia were assembled by fundamentally distinct geodynamic processes. Hence, the "supercontinent cycle" may have a more complex origin than previously considered.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.395
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0990.004

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 head0.030
GPT teacher head0.274
Teacher spread0.244 · 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

Citations65
Published2005
Admission routes1
Has abstractyes

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