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Record W4229847860 · doi:10.5194/essdd-2-281-2009

Arctic Ocean data in CARINA

2009· preprint· en· W4229847860 on OpenAlexaff
Sara Jütterström, Leif G. Anderson, Nicholas R. Bates, R. G. J. Bellerby, Truls Johannessen, E. Peter Jones, Robert M. Key, X. Lin, Are Olsen, Abdirahman M Omar

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicOcean Acidification Effects and Responses
Canadian institutionsBedford Institute of OceanographyFisheries and Oceans Canada
FundersNational Oceanic and Atmospheric AdministrationNorges Forskningsråd
KeywordsAlkalinityArcticEnvironmental scienceThe arcticSilicateNitrateCarbon fibersNutrientLinear regressionData setQuality (philosophy)Dissolved organic carbonTotal inorganic carbonOceanographyComputer scienceGeologyMathematicsStatisticsChemistryCarbon dioxideEcologyAlgorithmBiology

Abstract

fetched live from OpenAlex

Abstract. The paper describes the steps taken for quality controlling chosen parameters within the Arctic Ocean data included in the CARINA data set and checking for offsets between the individual cruises. The evaluated parameters are the inorganic carbon parameters (total dissolved inorganic carbon, total alkalinity and pH), oxygen and nutrients: nitrate, phosphate and silicate. More parameters can be found in the CARINA data product, but were not subject to a secondary quality control. The main method in determining offsets between cruises was regional multi-linear regression, after a first rough basin-wide deep-water estimate of each parameter. Lastly, the results of the secondary quality control are discussed as well as suggested adjustments.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.043
GPT teacher head0.269
Teacher spread0.226 · 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.

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

Citations12
Published2009
Admission routes1
Has abstractyes

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