MétaCan
Menu
Back to cohort
Record W2614322095 · doi:10.3724/sp.j.1085.2011.00246

Distributions of dissolved inorganic carbon and total alkalinity in the Western Arctic Ocean

2011· article· en· W2614322095 on OpenAlexaboutno aff

Bibliographic record

VenueADVANCES IN POLAR SCIENCE · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsAlkalinityDissolved organic carbonTotal inorganic carbonArcticCarbon fibersThe arcticEnvironmental scienceOceanographyEnvironmental chemistryChemistryCarbon dioxideGeologyMathematics

Abstract

fetched live from OpenAlex

The third Chinese National Arctic Research Expedition (3rd CHINARE-Arctic in 2008) was carried out from July to September 2008. During the survey, numerous sea water samples were taken for CO<sub>2</sub> parameter measurement (including total alkalinity TA and total dissolved inorganic carbon DIC).The distribution of CO<sub>2</sub> parameters in the Western Arctic Ocean was determined, and the controlling factors are addressed. The ranges of summertime TA, normalized TA (nTA), DIC and normalized DIC (nDIC) in the surface seawater were 1 757-2 229 μmol·kg<sup>-1</sup>, 2 383-2 722 μmol·kg<sup>-1</sup>, 1 681-2 034 μmol·kg<sup>-1</sup>, 2 119-2 600 μmol·kg<sup>-1</sup>, respectively. Because of dilution from ice meltwater, the surface TA and DIC concentrations were relatively low. TA in the upper 100 m to the south of 78°N had good correlation with salinity, showing a conservative behavior. The distribution followed the seawater-river mixing line at salinity >30, then followed the seawater mixing line (diluted by river water to salinity = 30) with the ice meltwater. The DIC distribution in the Chukchi Sea was dominated by biological production or respiration of organic matter, whereas conservative mixing dominated the mixed layer TA distribution in the ice-free Canada Basin.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.003
Threshold uncertainty score0.628

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.225
Teacher spread0.215 · 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 teacher head, 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

Citations1
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueADVANCES IN POLAR SCIENCESame topicArctic and Antarctic ice dynamicsFrench-language works237,207