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Record W7090423904 · doi:10.5281/zenodo.17309770

Figure data for "Review of the Radon Tracer Method for GHG emission estimates: development, application guidelines, improvements, and caveats" by Chambers et al.

2025· dataset· en· W7090423904 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typedataset
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsnot available
Fundersnot available
KeywordsAtmospheric researchEnvironmental researchGreenhouse gasRadonClimate changeAtmospheric emissionsClimate systemGlobal warming

Abstract

fetched live from OpenAlex

This dataset is a summary of source data for all figures in the manuscript "Review of the Radon Tracer Method for GHG emission estimates: development, application guidelines, improvements, and caveats" submitted to Atmospheric Measurement Techniques in Oct 2025. Contributing authors: Scott D. Chambers1, Ute Karstens2, Alan D. Griffiths1, Stefan Röttger3, Arnoud Frumau4, Christopher T. Roulston5, Peter Sperlich6, Felix Vogel7, Agnieszka Podstawczyńska8, Dafina Kikaj9, Maksym Gachkivskyi10, Michel Ramonet11, Blagoj Mitrevski5, Janja Vaupotič12, Xuemeng Chen13, Annette Röttger3 1ANSTO Environment Research & Technology Group, Lucas Heights, 2234, Australia 2ICOS ERIC Carbon Portal, Lund University, Lund, 22362, Sweden 3Physikalisch-Technische Bundesanstalt, Braunschweig, 38116, Germany 4Netherlands Organisation for Applied Scientific Research (TNO), Petten, 1755 LE, Netherlands 5CSIRO Environment, Aspendale, 3195, Australia 6New Zealand Institute for Earth Science Ltd., Hataitai, Wellington, 6021, New Zealand 7Climate Research Division, Environment and Climate Change Canada (ECCC), Toronto, ON, M3H 5T4, Canada 8Department of Meteorology and Climatology, University of Lodz, Łódź, 90-139, Poland 9National Physical Laboratory, Teddington, TW11 0LW, UK 10Institut für Umweltphysik, Heidelberg University, Heidelberg, 69120, Germany 11Laboratoire des Sciences du Climat et de l'Environnement, Université Paris-Saclay, 91191 Gif-sur-Yvette, France 12Department of Environmental Sciences, Jožef Stefan Institute, Ljubljana, SI-1000, Slovenia 13Institute for Atmospheric and Earth System Research (INAR), University of Helsinki, Helsinki, FIN-00014, Finland

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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.059
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.148
GPT teacher head0.450
Teacher spread0.301 · 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 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
Published2025
Admission routes1
Has abstractyes

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