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Record W6964844363 · doi:10.25921/b44k-xr97

Water temperature, salinity, and others taken by CTD, ADCP, and other instrumentation from research vessel icebreaker Xue Long in the North Pacific Ocean, Bering Sea, and Arctic Ocean from 2016-07-11 to 2016-09-26 (NCEI Accession 0221192)

2020· dataset· en· W6964844363 on OpenAlexaboutno aff

Bibliographic record

VenueNational Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information (NCEI) · 2020
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicEvolution and Paleontology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsArcticResearch vesselCruiseMarine researchMarine ecosystemMarine geologyThe arcticOcean chemistrySea ice

Abstract

fetched live from OpenAlex

This dataset contains water temperature, salinity, and others taken by CTD, ADCP, and other instrumentation from research vessel icebreaker Xue Long in the North Pacific Ocean, Bering Sea, and Arctic Ocean. The 7th Chinese Arctic Research Expedition targets on the global climate change and the correlations of sea ice variation, as well as its effects on the environment and ecosystem in Arctic Ocean. The major studies are focused on physical oceanography, marine chemistry, marine geology and marine ecology. The objectives of the studies are: 1) Investigation of primary path of pacific waters and land-derived fresh waters input to Canada Basin; 2) Observation on marine chemical parameters in Arctic Ocean and the influences on cycling of biogeochemistry. 3) Identification of plankton species and bio-diversity in Arctic area. The cruise was carried out during 11 July to 26 September, 2016. The field work in the U.S. EEZ was a part of this cruise. During the field work in the U.S. EEZ, observations/measurements of physical oceanography, meteorology, marine chemistry, marine Biology and marine geology are occupied in the Bering Sea and the Chukchi Sea. These data are part of the World Data Service for Oceanography and U.S State Department Marine Research dataset U2016-024. Data are in XLSX, HEX, binary formats. XLSX were converted into CSV.

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)0.002
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.075
Threshold uncertainty score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0200.018

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 head0.266
Teacher spread0.243 · 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
GenreDataset

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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueNational Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information (NCEI)Same topicEvolution and Paleontology StudiesFrench-language works237,207