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Comment on egusphere-2023-2981

2024· peer-review· en· W4391293300 on OpenAlexaff

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsUniversity of British ColumbiaUniversité du Québec à Rimouski
Fundersnot available
KeywordsChemistryEnvironmental science

Abstract

fetched live from OpenAlex

Abstract. A growing body of observations reveals rapid changes in both the total inventory and distribution of marine oxygen over the later half of the 21st century, leading to increased interest in extending oxygenation records into the past. Use of paleo-oxygen proxies have the potential to extend the spatial and temporal range of current records, bound pre-anthropogenic baselines, provide datasets necessary to test climate models under different boundary conditions, and ultimately understand how ocean oxygenation responds beyond decadal scale changes. This review seeks to summarize the current state-of-knowledge about proxies for reconstructing Cenozoic marine oxygen: sedimentary features, sedimentary redox-sensitive trace elements and isotopes, biomarkers, nitrogen isotopes, foraminiferal trace elements, foraminifera assemblages, foraminifera morphometrics, and benthic foraminifera carbon isotope gradients. Taking stock of each proxy reveals some common limitations in that the majority of proxies function best at low-oxygen concentrations and many reflect multiple environmental drivers. We also highlight recent breakthroughs in geochemistry and proxy approaches for constraining pelagic (in addition to benthic) oxygenation that are rapidly advancing the field. In light of both the emergence of new proxies and the persistent multiple driver problem, the need for multi-proxy approaches and FAIR data storage and sharing is emphasized. Continued refinement of proxy approaches and both proxy-proxy and proxy-model comparisons are likely to support the growing needs of both oceanographer and paleoceanographers interested in paleo-oxygenation records.

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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.444
Threshold uncertainty score0.793

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0150.008
Insufficient payload (model declined to judge)0.4440.312

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 head0.036
GPT teacher head0.285
Teacher spread0.249 · 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.

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
Published2024
Admission routes1
Has abstractyes

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