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Record W7097469339

with an improved hydrous titanium oxide technique at the Sudbury Neutrino Observatory

2013· article· en· W7097469339 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNeutrino Physics Research
Canadian institutionsnot available
Fundersnot available
KeywordsTitaniumImpurityObservatoryAnalytical Chemistry (journal)Heavy waterOxideTitanium oxideAdsorption
DOInot available

Abstract

fetched live from OpenAlex

The existing hydrous titanium oxide (HTiO) technique for the measurement of 224 Ra and 226 Ra in the water at the Sudbury Neutrino Observatory (SNO) has been changed to make it faster and less sensitive to trace impurities in the HTiO eluate. Using HTiO-loaded filters followed by cation exchange adsorption and HTiO co-precipitation, Ra isotopes from 200-450 tonnes of heavy water can be extracted and concentrated into a single sample of a few millilitres with a total chemical efficiency of 50%. Combined with beta-alpha coincidence counting, this method is capable of measuring 2.0×10 −3 µBq/kg of 224 Ra and 3.7×10 −3 µBq/kg of 226 Ra from the 232 Th and 238 U decay chains, respectively, for a 275 tonne D2O assay, which are equivalent to 5×10 −16 g Th/g and 3×10 −16 g U/g in heavy water.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.994
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.015
GPT teacher head0.253
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

Citations0
Published2013
Admission routes1
Has abstractyes

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