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Record W4389959603 · doi:10.2138/gselements.19.5.289

Impacts of Large-scale Magmatism on Land Plant Ecosystems

2023· article· en· W4389959603 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueElements · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsGeological Survey of CanadaNatural Resources Canada
FundersNatural Resources CanadaAarhus Universitets ForskningsfondEuropean CommissionAarhus Universitet
KeywordsTerrestrial ecosystemExtinction eventMagmatismEarth scienceVegetation (pathology)EcosystemPalynologyGeologyTerrestrial plantExtinction (optical mineralogy)Scale (ratio)Physical geographyEcologyPollenPaleontologyGeographyBiologyTectonics

Abstract

fetched live from OpenAlex

Terrestrial ecosystems are integral components of global carbon budgets and modulators of Earth’s climate. Emplacement of large igneous provinces (LIPs) is implicated in almost every mass extinction and smaller biotic crises in Earth’s history, but the effects of these and other large-scale magmatic events on terrestrial ecosystems are poorly understood. Palynology, the study of fossilized pollen and spores, offer a means to robustly reconstruct the types and abundance of plants growing on the landscape and their response to Earth crises, permitting predictions of the response of terrestrial vegetation to future perturbations. We review existing palynological literature to explore the direct and cumulative impacts of large-scale magmatism, such as LIP-forming events, on terrestrial vegetation composition and dynamics over geological time.

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.

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 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 score0.015
Threshold uncertainty score0.998

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)0.0030.004

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 head0.019
GPT teacher head0.271
Teacher spread0.252 · 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