MétaCan
Menu
Back to cohort
Record W6969045157 · doi:10.5443/1844

OASIS-CANADA CFL: Atmospheric composition and structure during the CFL campaign from the Amundsen icebreaker in the Amundsen Gulf

2016· dataset· en· W6969045157 on OpenAlexaboutno aff

Bibliographic record

VenueCanadian Polar Data Network · 2016
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsSODARGlobal Positioning SystemResearch vesselWind profilerMode (computer interface)Absorption (acoustics)Ozone depletion

Abstract

fetched live from OpenAlex

Data were compiled in campaign mode and were obtained over the ice of the Amundsen Gulf. Chemical and meteorological variables were collected with commercial and custom made instrumentation, as detailed below. Ozone (O3): Measurements were taken with TECO TEI049 instrument and five-minute averaged data with filtered generator influence are archived in one file. Wind components and their vertical profile: Wind data were collected by Sodar model Scintec MFAS SN A-C-0073 with software version APRun 1.13. Reported data are at interval of 0.25hour. GPS record is embedded into Sondar data record. In addition, the following data sets have been created by collaborators: (1) Zone vertical profile with home built differential absorption LIDAR (Jim Whiteway, York University, Toronto, whiteway@yorku.ca); (2) BrO MAXDOAS (multiaxis differential optical absorption spectroscopy) and LPDOAS (long pass active differential optical absoprtion spectroscopy) (Udo Frieß and Denis Poehler, University of Heidelberg, Germany, udo.friess@iup.uni-heidelberg.de, denis.poehler@iup.uni-heidelberg.de); (3) BrO by chemical trapping followed by GC/EC analysis (Paul Shepson, Purdue University, USA, pshepson@purdue.edu). GPS locations are available in D. Barber et al., Atmosphere-Ocean 48, Issue 4, pp. 225-243, 2010.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0060.001

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 head0.203
Teacher spread0.194 · 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 designObservational
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
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Polar Data NetworkFrench-language works237,207