MétaCan
Menu
← Back to cohort
Record W6945840886 · doi:10.25921/gwgr-a071

Dissolved inorganic carbon (DIC), total alkalinity (TA), nutrients, dissolved oxygen, water temperature, salinity and other measurements collected from discrete samples and profile observations during the R/V Dana Davis Strait Observing System cruise 2372 (EXPOCODE 26D420200830) in Davis Strait, Baffin Bay, Labrador Sea, North Pacific Ocean from 2020-08-30 to 2020-09-14 (NCEI Accession 0291293)

2024· dataset· en· W6945840886 on OpenAlexaffabout

Bibliographic record

VenueNational Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information (NCEI) · 2024
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsBedford Institute of Oceanography
Fundersnot available
KeywordsCruiseAlkalinitySalinityTotal inorganic carbonSampling (signal processing)Water qualityDissolved organic carbonNutrient

Abstract

fetched live from OpenAlex

Oceanographic sampling of physical, chemical, and biological parameters was conducted along selected fixed sections in Davis Strait, Baffin Bay, Labrador Sea, North Atlantic Ocean at full water depths during the R/V Dana Davis Strait Observing System (DSOS) cruise (EXPOCODE 26D420200830) from 2020-08-30 to 2020-09-14. The cruise is part of DSOS's long-term, high-frequency repeat program. CTD casts were performed at all stations, and discrete water samples were collected in Niskin bottles using the CTD/Rosette system. It was designed to investigate Arctic-North Atlantic interactions, including the variability and trend of freshwater, heat, carbon, oxygen, and nutrient fluxes, as well as ecosystem responses to climate change. This effort was conducted in support of the NSF (OPP1902595) and Fisheries and Oceans, Canada (OFSI).

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)0.001
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: Dataset · Consensus signal: none
Teacher disagreement score0.809
Threshold uncertainty score0.380

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.016
GPT teacher head0.228
Teacher spread0.212 · 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
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueNational Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information (NCEI)→Same topicGenomics and Phylogenetic Studies→French-language works237,207→