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Record W6930971685 · doi:10.5281/zenodo.15387918

Single-Channel Tricolour Absorption Photometer (STAP) measurements of aerosol absorption coefficients in summertime in Narsaq, South Greenland during Greenfjord 2023

2025· dataset· en· W6930971685 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typedataset
Languageen
FieldNeuroscience
TopicNeurogenesis and neuroplasticity mechanisms
Canadian institutionsImpact
Fundersnot available
KeywordsAerosolAbsorption (acoustics)PhotometerFlag (linear algebra)Filter (signal processing)Sun photometerWavelengthSample (material)Attenuation

Abstract

fetched live from OpenAlex

Abstract and dataset contents: This dataset contains measurements of aerosol absorption coefficients at 450, 525 and 624 nm using a Single-channel Tricolour Absorption Photometer (STAP, Brechtel Manufacturing Inc. USA), which measures the attenuation of light through a sample filter at multiple wavelengths and compares this to a reference filter. Measurements were conducted at Narsaq International Research Station (NIRS), centrally located in Narsaq, Southern Greenland (lat: 60.9157503°, lon: -46.0533263°, alt: 17 m above sea level), during the Greenfjord campaign in June-August 2023. Metadata can be found in the file 'metadata_STAP.docx'. Briefly, the dataset files (Lv2_STAP.csv) include: Datetime Absorption coefficients at 450, 525 and 624 nm (M m-1) Pollution flag to inform data user when short-lived spikes can be found in the data from local anthropogenic pollution Inlet relative humidity (RH) flag to inform the data user when the RH in the inlet system reached over 40 % Filter usage flag to inform data user of the sample filter usage per wavelength due to different responses to filter loading at each wavelength Grounding flag to inform user when the instrument was not electrically grounded and therefore a larger signal-to-noise ratio is expected Funding acknowledgements: This work was supported by funding from the Swiss National Science Foundation grant no. 200021_212101, the Swiss Polar Institute grant no. SPI-FLAG-2021-002 Greenfjord, and the ENAC Flagship 2022 ECO-Plains.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.272
Threshold uncertainty score0.542

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.003

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 head0.088
GPT teacher head0.267
Teacher spread0.179 · 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
Published2025
Admission routes1
Has abstractyes

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