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Comment on egusphere-2025-1106

2025· peer-review· en· W4413064972 on OpenAlexaff

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsOceanographyGeology

Abstract

fetched live from OpenAlex

Abstract. Mediterranean climate is characterised by a strong seasonality, critical for the ecosystems and societies in the region and is susceptible to climate change. The timing of when the Mediterranean climate developed over the past few thousand years remains a complex and unresolved question. Most studies document a part of the Mediterranean area or are based on a single (and frequently different) climate reconstruction method which can lead to non-negligible biases when considering climate changes on a Mediterranean scale. Several climate summaries based on pollen data have recently been produced on a European scale. However, none of them has focused exclusively on the Mediterranean area, except two recent syntheses documenting the eastern and western parts of the Mediterranean basin. We aimed to document the climate changes of the central Mediterranean during the Holocene, the trends and the different patterns. A robust methodology has been applied to 38 pollen records spreading across the south of France and Italy. Four climate reconstruction methods based on different mathematical and ecological concepts have been tested (MAT, WA-PLS, BRT and RF) and the selection of the best modern calibration dataset has also been investigated to produce the most reliable results. Particular attention has been paid to the seasonal nature of climatic parameters (winter and summer temperatures and precipitations). A model-data comparison has been made using transient model simulation TraCE-21ka in an attempt to gain a better understanding of the climate mechanisms and their forcing. Our palaeoclimate reconstruction shows that during the mid Holocene, summer temperatures were colder in the southern part of the central Mediterranean region albeit associated with positive anomalies, which is in accordance with the summer temperature reconstructions of the Iberian peninsula and eastern Mediterranean for the mid Holocene. In northern parts of the central Mediterranean region, and particularly in high elevation (> 1000 m), a Holocene thermal maximum is present, contrasting with the cold summer temperature anomalies previously reconstructed with pollen data for the Mediterranean region. Holocene summer conditions were characterised by specific spatio-temporal patterns, i.e., a west-east differentiation in southern France and a north-south one in Italy, for both temperature and precipitation. Holocene winter conditions showed a more homogeneous spatio-temporal pattern, i.e., general humidification and warming through the Holocene for Italy and southern France. A data-model simulation comparison shows a mostly coherent signal in winter but an incoherent one in summer. Those discrepancies between model simulations and pollen-based reconstructions suggest that during the Holocene, the northern Mediterranean climate was already subject to a marked spatio-temporal variability, particularly in summer, that cannot only be explained by changes in orbital configuration and atmospheric greenhouse gas evolution. Finally, our result highlighted the onset of the "Mediterraneanization" of the central Mediterranean region, characterised by wet winters and dry summers, after 8,000 years BP. The "Mediterraneanization" process seems to have had a greater impact on the southern regions than on the northern regions.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.293
Threshold uncertainty score0.979

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0140.007
Insufficient payload (model declined to judge)0.2930.190

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 head0.063
GPT teacher head0.399
Teacher spread0.335 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2025
Admission routes1
Has abstractyes

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