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Record W1981002749 · doi:10.1109/icsens.2011.6127315

Sensitive, fast-responding passive electrostatic radon monitor

2011· article· en· W1981002749 on OpenAlexafffund
Ryan Griffin, A. Kochermin, N. G. Tarr, H. McIntosh, Hao Ding, Joel C. Weber, R. Falcomer

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadiation Detection and Scintillator Technologies
Canadian institutionsHealth CanadaInstitute for Microstructural SciencesCarleton University
FundersNational Research Council CanadaHealth Canada
KeywordsDetectorRadonElectronicsTransient (computer programming)OptoelectronicsPhysicsMaterials scienceOpticsElectrical engineeringComputer scienceEngineeringNuclear physics

Abstract

fetched live from OpenAlex

A second generation fast-responding passive radon detector using electrostatic concentration and enhanced readout electronics has been designed, built and tested. This detector utilizes the custom α-detecting IC called αRAM. In order to assess the response time, simulations were performed to analyze the turn-on transient of the detector. In an ambient with constant radon concentration, simulations indicate 1.44 hours will be required for the detector to reach 90% of its maximum count rate. This result is consistent with experimental findings using both first and second generation passive radon detectors.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.890
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.013
GPT teacher head0.230
Teacher spread0.217 · 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 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

Citations8
Published2011
Admission routes2
Has abstractyes

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