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Record W2802881856 · doi:10.1144/sp470.16

Supercontinents: myths, mysteries, and milestones

2018· article· en· W2802881856 on OpenAlexaff
Daniel Pastor‐Galán, R. Damian Nance, J. Brendan Murphy, Christopher J. Spencer

Bibliographic record

VenueGeological Society London Special Publications · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsSt. Francis Xavier University
FundersJapan Society for the Promotion of Science
KeywordsGeologyMythologyPaleontologyAstrobiologyEarth scienceHistoryClassics

Abstract

fetched live from OpenAlex

Abstract There is an emerging consensus that Earth's landmasses amalgamate quasi-periodically into supercontinents, interpreted to be rigid super-plates essentially lacking tectonically active inner boundaries and showing little internal lithosphere–mantle interactions. The formation and disruption of supercontinents have been linked to changes in sea-level, biogeochemical cycles, global climate change, continental margin sedimentation, large igneous provinces, deep mantle circulation, outer core dynamics and Earth's magnetic field. If these hypotheses are correct, long-term mantle dynamics and much of the geological record, including the distribution of natural resources, may be largely controlled by these cycles. Despite their potential importance, however, many of these proposed links are, to date, permissive rather than proven. Sufficient data are not yet available to verify or fully understand the implications of the supercontinent cycle. Recent advances in many fields of geoscience provide clear directions for investigating the supercontinent cycle hypothesis and its corollaries but they need to be vigorously pursued if these far-reaching ideas are to be substantiated.

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 score0.212
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0560.001

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 head0.016
GPT teacher head0.212
Teacher spread0.196 · 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

Citations61
Published2018
Admission routes1
Has abstractyes

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