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Record W2038430508 · doi:10.1118/1.3476171

Poster - Thur Eve - 66: Investigation of Shielding Property Changes in Curing High Density Concrete

2010· article· en· W2038430508 on OpenAlexaff
M Marsh, Charles C. Peters, N Rawluk, L J Schreiner

Bibliographic record

VenueMedical Physics · 2010
Typearticle
Languageen
FieldMaterials Science
TopicGraphite, nuclear technology, radiation studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsElectromagnetic shieldingMaterials scienceAttenuationBunkerComposite materialProperty valueHalf-value layerBeam (structure)Curing (chemistry)OpticsRadiation shieldingPhysics

Abstract

fetched live from OpenAlex

Our centre is currently undergoing a major expansion, including the construction of two new linear accelerator radiotherapy bunkers and the addition of extra shielding to existing bunkers. While shielding material is typically specified by Tenth-Value Layer (TVL) at the design stage, the concrete supplier will specify the (wet) densities of the concrete constituents, and the concrete testing lab will verify the as-cast material by its dry (cured) density. Thus, the relationship between the intended TVL and the actual performance of the shielding material might not be entirely clear. In this study, cylindrical samples of the high-density shielding concrete were taken as each section was poured. The shielding performance of the samples (measured by beam attenuation and TVL) was evaluated for 15 MV and 6 MV X-ray beams, and for the 1.25 MeV monoenergetic gamma beam from a Cobalt-60 (Co-60) source. The samples were also imaged and analyzed using Cobalt-60 Cone Beam Computed Tomography (CoCBCT). Results indicate no significant change in the TVL of high-density concrete samples as they cure. The minor fluctuations in shielding properties observed are explained by the heterogeneous structure of the samples as indicated in the CoCBCT images.

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 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 score0.076
Threshold uncertainty score0.279

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)0.0000.000

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 head0.019
GPT teacher head0.240
Teacher spread0.221 · 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.

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

Citations0
Published2010
Admission routes1
Has abstractyes

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