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Record W2780794709 · doi:10.1525/elementa.272

Commentary on the outputs and future of Biogeochemical Exchange Processes at Sea-Ice Interfaces (BEPSII)

2017· article· en· W2780794709 on OpenAlexaff
Nadja Steiner, Jacqueline Stefels

Bibliographic record

VenueElementa Science of the Anthropocene · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsBiogeochemical cycleSea iceEnvironmental scienceEarth system scienceOceanographyCryosphereEarth scienceClimatologyGeologyEcologyBiology

Abstract

fetched live from OpenAlex

Biogeochemical processes associated with sea ice are still inadequately described and poorly represented in models, making it difficult to properly quantify the impacts of climate change in polar regions. Within the framework of the international Scientific Committee of Ocean Research (SCOR) working group 140, BEPSII, a community of sea-ice biogeochemical scientists established guidelines for the measurement of biogeochemical processes in sea ice, collated observed data, synthesized knowledge of sea-ice biogeochemical processes, and identified the feedbacks between biogeochemical and physical processes at the terrestrial-ocean-ice-snow-atmosphere interfaces and within the sea-ice matrix. Many of these results are presented in Elementa’s Special Feature on BEPSII. By bringing together experimentalists and modelers, major improvements of sea-ice biochemistry models have been achieved which are anticipated to affect models on micro- to global scales. However, large gaps still exist in our understanding of detailed biogeochemical processes in sea ice, their seasonal evolution and their interactions with surrounding environments. The BEPSII community recommends continued focus on the development of reproducible methods and techniques for reliable inter-study comparisons, to enhance our understanding in areas where gaps have been identified via coordinated process studies combining modeling tools, laboratory experiments and field studies, and on the use of such studies to develop conceptual models helping us to understand the overall system.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.405
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.257
Teacher spread0.240 · 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; both teacher heads agree on what is shown here.

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

Citations8
Published2017
Admission routes1
Has abstractyes

Explore more

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