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Record W4402178882 · doi:10.1101/2024.09.02.610915

A paleogenomic approach to reconstruct historical responses of coral reefs to anthropogenic change

2024· preprint· en· W4402178882 on OpenAlexaff
Raúl A. González‐Pech, Colin Howe, Luis Lizcano-Sandoval, Raphael Eisenhofer, Stephanie Marciniak, Sofia Roitman, Ángela M. Marulanda-Gómez, A Ramírez, George H. Perry, Laura S. Weyrich, Mateo López‐Victoria, Julia E. Cole, Mónica Medina

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCoral reefCoralReefOceanographyResilience of coral reefsCoral reef organizationsEnvironmental issues with coral reefsGeographyEnvironmental scienceGeologyEnvironmental resource managementCoral reef protection

Abstract

fetched live from OpenAlex

Abstract Coral reefs are declining worldwide due to anthropogenic environmental change. The foundation and health of these ecosystems rely on the harmonious functioning of all members of coral holobionts, i.e., cnidarian host, symbiotic microalgae, and associated microbiome. Coral stress responses often involve shifts in the taxonomic identity of their symbionts and microbiomes. Tracing back changes in coral holobiont composition over prolonged time periods can help us reconstruct health history of reefs and gain a better understanding of coral response to current stressors. Here, we focused on a major Caribbean reef-builder coral, Orbicella faveolata , from Varadero Reef, Colombia. This reef has undergone extensive freshwater sediment discharge and pollution for decades as result of urbanization. We show, for the first time, that paleogenomic and paleoclimatic approaches can be combined to reconstruct historical coral holobiont dynamics potentially associated with anthropogenic disturbances.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0060.005
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.034
GPT teacher head0.227
Teacher spread0.193 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)→Same topicCoral and Marine Ecosystems Studies→French-language works237,207→