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Record W3033015451 · doi:10.1029/2020gl088898

Platelet Ice Under Arctic Pack Ice in Winter

2020· article· en· W3033015451 on OpenAlexaff
Christian Katlein, Volker Mohrholz, Igor Sheikin, Polona Itkin, Dmitry Divine, Julienne Strœve, Arttu Jutila, Daniela Krampe, Egor Shimanchuk, Ian Raphael, Benjamin Rabe, Ivan Kuznetsov, Maria Mallet, Hailong Liu, Mario Hoppmann, Ying‐Chih Fang, Adela Dumitrascu, Stefanie Arndt, Philipp Anhaus, Marcel Nicolaus, Ilkka Matero, Marc Oggier, Hajo Eicken, Christian Haas

Bibliographic record

VenueGeophysical Research Letters · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversity of Manitoba
FundersBundesministerium für Bildung und ForschungDeutsche ForschungsgemeinschaftNatural Environment Research CouncilNorges ForskningsrådSight Research UK
KeywordsArctic ice packSea iceAntarctic sea iceIce formationDrift iceGeologyArcticOceanographyCryosphereFast iceSea ice thicknessIce shelfClimatologyAtmospheric sciences

Abstract

fetched live from OpenAlex

Abstract The formation of platelet ice is well known to occur under Antarctic sea ice, where subice platelet layers form from supercooled ice shelf water. In the Arctic, however, platelet ice formation has not been extensively observed, and its formation and morphology currently remain enigmatic. Here, we present the first comprehensive, long‐term in situ observations of a decimeter thick subice platelet layer under free‐drifting pack ice of the Central Arctic in winter. Observations carried out with a remotely operated underwater vehicle (ROV) during the midwinter leg of the MOSAiC drift expedition provide clear evidence of the growth of platelet ice layers from supercooled water present in the ocean mixed layer. This platelet formation takes place under all ice types present during the surveys. Oceanographic data from autonomous observing platforms lead us to the conclusion that platelet ice formation is a widespread but yet overlooked feature of Arctic winter sea ice growth.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

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

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 head0.040
GPT teacher head0.280
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; 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 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

Citations39
Published2020
Admission routes1
Has abstractyes

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Same venueGeophysical Research LettersSame topicArctic and Antarctic ice dynamicsFrench-language works237,207