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Record W2124588332 · doi:10.1111/gto.12043

Early Silurian ‘algal meadows’ of Anticosti Island, eastern Canada: an analogue to modern sea grass meadows?

2014· article· en· W2124588332 on OpenAlexaffabout
Yi Wang, Jisuo Jin, Renbin Zhan, Paul Copper

Bibliographic record

VenueGeology Today · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsWestern University
Fundersnot available
KeywordsAlgaeAcritarchPaleozoicEcologyGeologyPaleontologyOceanographyBiology

Abstract

fetched live from OpenAlex

In modern marine ecosystems, sea‐grass and chlorophyte meadows play an important ecological role by serving as a carbon sink. Despite their generally limited areal distribution, the high productivity of sea‐grass meadows makes them an efficient assimilator of CO2. During the early Palaeozoic, complex life was virtually confined to the marine environment, with algae being one of the common carbon‐fixers, alongside abundant calcifying cyanobacteria, rhodophytes, chlorophytes and charophytes, as well as non‐skeletal dinoflagellates and acritarchs. Fossil and molecular data indicate that marine thallophytic algae first appeared in the Early Proterozoic and became widespread in the Palaeozoic, although their fossil record is sporadic because of their soft‐bodied nature; in the absence of angiosperm sea grass and mangroves and poorly understood phytoplankton biomass, thallophytic algae were probably major primary producers. In this article, we suggest that thallophytic algae may have played a significant role as a carbon sink in the Early Silurian, analogous to modern sea‐grass meadows or kelp forests, based on the well‐preserved Early Silurian thallophytic algal meadow from Anticosti Island, eastern Canada.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.002
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.185
Teacher spread0.176 · 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

Citations1
Published2014
Admission routes2
Has abstractyes

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