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Record W1610815324 · doi:10.1139/p01-145

Gamma-ray transmission technique for quality control of coal seams

2002· article· en· W1610815324 on OpenAlexvenueno aff
N Raja Sekhar, SV SR Reddy, Ashwath S. Rao

Bibliographic record

VenueCanadian Journal of Physics · 2002
Typearticle
Languageen
FieldEngineering
TopicAdvanced X-ray and CT Imaging
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsCoalAttenuationGamma rayCarbon fibersFigure of meritMoistureTransmission (telecommunications)Sample (material)OpticsComposite materialNuclear physicsWaste managementMaterials scienceMeteorologyThermodynamicsElectrical engineering

Abstract

fetched live from OpenAlex

The useful heat value (UHV) that is the figure of merit for coal depends on various parameters such as fixed carbon, volatiles, ash, and moisture. The percentage of these materials present in a given sample of coal can be estimated by gamma-ray transmission studies. Using gamma rays of energies 30.85 and 81.0 keV, coal samples were studied and the relationships between attenuation coefficients and known UHV and ash contents were obtained. These relationships can be used to measure UHV/ash values for other samples using this simple, fast, and reliable nondestructive method. PACS No.: 32.80

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score0.359

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 head0.016
GPT teacher head0.234
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.

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
Published2002
Admission routes1
Has abstractyes

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