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Record W2617509417

Canada Carbon vein graphite tests show nuclear potential

2014· article· en· W2617509417 on OpenAlex
E. D. Hughes

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIndustrial Minerals · 2014
Typearticle
Languageen
FieldMaterials Science
TopicGraphite, nuclear technology, radiation studies
Canadian institutionsnot available
Fundersnot available
KeywordsGraphitePebbleCarbon fibersNuclear graphiteSilicon carbideMaterials scienceNuclear industryCarbideMetallurgyWaste managementNuclear engineeringComposite materialEngineeringGeology
DOInot available

Abstract

fetched live from OpenAlex

Following our earlier metallurgical testing at SGS Lakefield, which yielded graphite as pure as could be determined by their analytical method, a sample of that same material was shown to be of nuclear-grade purity (...), said Canada Carbon CEO, Bruce Duncan. Both synthetic graphite and natural vein graphite have commonly been used in the nuclear industry in traditional reactors. This has provided the graphite industry with a niche but high value market. New generation designs feature pebble shells - nuclear fuel coated with silicon carbide, natural, synthetic and recycled graphite layers that moderate the reaction speed - which carry nuclear fuel into the reactor. These pebble-bed reactors could use significantly more graphite than today's industry and could provide future, high purity suppliers with a significant market opportunity.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.839
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.018
GPT teacher head0.210
Teacher spread0.192 · 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