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Record W2513057828 · doi:10.1111/pala.12258

How far did feedback between biodiversity and early diagenesis affect the nature of Early Palaeozoic sea floors?

2016· article· en· W2513057828 on OpenAlexfundno aff
V. Paul Wright, Lesley Cherns

Bibliographic record

VenuePalaeontology · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Stratigraphy of Fossils
Canadian institutionsnot available
FundersQueen's University
KeywordsOrdovicianPaleozoicGeologyPaleontologyDiagenesisCarbonateBioturbationPrecambrianPhanerozoicCarbonate platformDevonianSedimentSedimentary depositional environmentCenozoic

Abstract

fetched live from OpenAlex

Abstract Latest Precambrian to Early Palaeozoic biosphere evolution triggered changes in early diagenesis and carbonate precipitation which fed back to biodiversity through colonization of hard substrates. Progressive increase in the depth and intensity of bioturbation and bio‐irrigation lowered the zone of early carbonate cementation in the uppermost sediment column. This firstly led to a decline in the abundance of the flat‐pebble conglomerates which had been a common feature of Cambrian and Early Ordovician successions, replaced by the peak and subsequent decline in the Palaeozoic abundance of submarine hardgrounds. The availability of very widespread lithified sea floors in shallow subtidal settings during the Ordovician promoted a rapid expansion in sclerobiont diversity and contributed to the Great Ordovician Biodiversification Event.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.012
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.014
GPT teacher head0.208
Teacher spread0.194 · 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

Citations39
Published2016
Admission routes1
Has abstractyes

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