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Record W6913044399 · doi:10.5281/zenodo.8406368

Mesoscale regionalisation of the western Antarctic Peninsula

2023· report· en· W6913044399 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typereport
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsRegionalisationPeninsulaMesoscale meteorologyContext (archaeology)Climate changeNova scotia

Abstract

fetched live from OpenAlex

As part of the One Ocean Expedition onboard the Statsraad Lehmkuhl, scientists from Argentina, Chile, Uruguay and Norway met for 10 days to discuss the Southern Ocean Action Plan (SOAP) in the context of the southern Scotia Arc and western Antarctic Peninsula. This geographical region represents an area of strong research and commercial interests for all the participating nationalities, and key questions from the SOAP were applied through this regional lens. The physical, ecological and anthropological complexity of the region coupled with the rapid and ongoing changes driven primarily by climate change mean that a “one management strategy fits all” approach is unlikely to be appropriate. It was agreed that a more ecologically realistic regionalisation is a necessary first step in understanding the distribution of threats, their impacts and how they are likely to change over time. At the conclusion of the meeting, the group agreed that there was sufficient scientific literature and motivation to write a peer-reviewed article outlining a putative bioregionalisation of the southern Scotia Arc and western Antarctic Peninsula, and such an article could be used as a reference point for future scientific collaborations and research proposal development.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.248
Threshold uncertainty score0.493

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.135
GPT teacher head0.289
Teacher spread0.154 · 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
GenreOther

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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)→Same topicRuminant Nutrition and Digestive Physiology→French-language works237,207→