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Record W4249333684 · doi:10.7287/peerj.preprints.26822

Sea ice biota: Excerpts from the State of the Arctic Marine Biodiversity Report by the Sea Ice Biota Expert Network/CBMP

2018· preprint· en· W4249333684 on OpenAlexaffabout
Haakon Hop, Bodil A. Bluhm, I. A. Melnikov, Michel Poulin, Mikko Vihtakari, R. Eric Collins, Rolf Gradinger, Thomas Juul‐Pedersen, Cecilie von Quillfeldt

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicOcean Acidification Effects and Responses
Canadian institutionsCanadian Museum of Nature
Fundersnot available
KeywordsSea iceBiotaArcticArctic ice packOceanographyArctic ecologyCryosphereEnvironmental scienceMarine ecosystemAntarctic sea iceEcosystemEcologyGeologyBiology

Abstract

fetched live from OpenAlex

Sea ice is an important Arctic habitat that supports a high diversity of species—with over 1276 protist taxa alone. Multi-year sea ice is being replaced by first-year ice and open water, which will cause shifts in ice algal communities with cascading effects on the ice-associated ecosystem. Documentation of ice biota composition, abundance and natural variability is critical for evaluating responses to the decline in Arctic sea ice. The Sea-ice Biota Expert Network, therefore, aggregated and reviewed data on status and trends of ice-associated Bacteria, Archaea, microalgae, meiofauna, and under-ice macrofauna Focal Ecosystem Components (FECs) across eight Arctic Marine Areas as well as current monitoring. Sea ice biota monitoring has occurred most frequently in the central Arctic, Svalbard area, Barrow (Alaska) and the Canadian Arctic, with recent sites in northern Greenland. Sea ice algal community structure has possibly changed in the central Arctic between the 1980s and 2010s, and ice-amphipod abundance and biomass have declined in the Svalbard area since the 1980s. Consistent monitoring protocols, equipment and methodology should be implemented. The presentation also evaluates dominant drivers of observed trends, and knowledge and monitoring gaps.

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)0.001
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: Review · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.009
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0250.015

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 head0.019
GPT teacher head0.222
Teacher spread0.203 · 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
GenreReview

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
Published2018
Admission routes2
Has abstractyes

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