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Record W4388661556 · doi:10.1088/1681-7575/ad0c9f

Ambient humidity, the overlooked influencer of radioactivity measurements

2023· article· en· W4388661556 on OpenAlexaff
S. Pommé, H Stroh, T. Altzitzoglou, J. Paepen, R. Van Ammel, M Marouli, L. Verheyen, Michael P. Unterweger, Ryan Fitzgerald, Denis E. Bergeron, L. Pibida, O. Nähle, Karsten Kossert, Nelson Ramírez, Emma Bendall, Andrew Fenwick, K M Ferreira, J D Keightley, M. Baker, S.M. Collins, C Michotte, S Courte, Romain Coulon, T W Jackson, W.M. van Wyngaardt, A. Fazio, P. De Felice, B. Vodenik, M. Korun, F. Juget, Claude Bailat, Youcef Nedjadi, François Bochud, Thierry Buchillier, T. Roy, R. Galea, Ivan Kajan, M.W. van Rooy, Philip McGinnity, I. Tucaković, I. Osvath, K. Pelczar

Bibliographic record

VenueMetrologia · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadioactive Decay and Measurement Techniques
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsAmplitudeHumidityExponential functionEnvironmental scienceExponential decayRelative humidityAtmospheric sciencesPhysicsStatisticsNuclear physicsMeteorologyMathematicsMathematical analysisOptics

Abstract

fetched live from OpenAlex

Abstract When verifying the validity of the exponential-decay law through 137 precise decay rate measurement series at various nuclear laboratories, minor violations have been observed in the shape of annual cycles in the residuals with different amplitudes and phase shifts. The timing and amplitude of these deviations have been compared with local weather data and it appears that ambient humidity is highly correlated with the observed instabilities in these radioactivity measurements. In fact, when compensating the residuals for a linear relationship with absolute humidity in air, most of the annual cycles are no longer statistically significant. As a result, the validity of the exponential-decay law can now be demonstrated with even higher fidelity.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.066
GPT teacher head0.304
Teacher spread0.238 · 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 designBench or experimental
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

Citations7
Published2023
Admission routes1
Has abstractyes

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