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Record W2980462435 · doi:10.1080/16742834.2020.1675137

Overview of the 9th Chinese National Arctic Research Expedition

2019· article· en· W2980462435 on OpenAlexaboutno aff
Zexun Wei, Hongxia Chen, Ruibo Lei, Xiaoguo Yu, Tao Zhang, Zhongxiang Tian, Yanpei Zhuang, Li Tao, Zhuoli Yuan

Bibliographic record

VenueAtmospheric and Oceanic Science Letters · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsOceanographyArcticThe arcticMarine geologyGeographyStructural basinPlateau (mathematics)RidgePhysical geographyGeologyPaleontologyCartography

Abstract

fetched live from OpenAlex

The 9th Chinese National Arctic Research Expedition was carried out from 20 July to 26 September 2018. The expedition was successful in undertaking multidisciplinary comprehensive surveys in the fields of physical oceanography, marine meteorology, sea ice, marine chemistry, marine biology, marine ecology, geology, and geophysics in the Bering Sea, Chukchi Sea, Chukchi Plateau, Mendeleev Ridge, and Canada Basin. This paper gives an overview of the main achievements of this expedition and highlights the scientific achievements.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.200
Threshold uncertainty score0.398

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.003

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 head0.023
GPT teacher head0.274
Teacher spread0.252 · 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
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

Citations11
Published2019
Admission routes1
Has abstractyes

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