MétaCan
Menu
Back to cohort

Relationship between average maximum and average arbitrary reflection values of coals vitrinite

2021· article· en· W3208563646 on OpenAlexaboutno aff
Yu. A. Zolotukhin, T. F. Kraskovskaya, V. V. Kuprygin

Bibliographic record

VenueFerrous Metallurgy Bulletin of Scientific Technical and Economic Information · 2021
Typearticle
Languageen
FieldEnergy
TopicCoal and Coke Industries Research
Canadian institutionsnot available
Fundersnot available
KeywordsVitriniteVitrinite reflectanceReflection (computer programming)Degree (music)MineralogyReflectivityMathematicsGeologyStatisticsStructural basinSource rockPhysicsPaleontologyOptics

Abstract

fetched live from OpenAlex

For a quantitative assessment of the degree of coalification of coals in different countries, either average arbitrary (R0,r) vitrinite reflectance or average maximum (R0,max) vitrinite reflectance are mainly used. Since these indicators differ markedly in magnitude, in many countries, equations of the relationship between them have been established relatively long time ago in order to compare correctly the technological properties of different coals of the same type by indicators R0,max or R0,r. For Russian coals, the relationship between the vitrinite reflection indices R0,max and R0,r has not yet been established. Based on the studies of 40 samples of coals from Russia (Kuznetsk Basin), equations of the relationship between the average maximum (R0,max) and average arbitrary (R0,r) reflection values of coals vitrinite were obtained, taking into account the degree of their genetic recovery. The accuracy of calculating the indicator R0,max through R0,r at that is higher when taking into account the degree of genetic recovery of coals, which was 0.03%, versus 0.04% without accounting it. To compare technological properties of Russian coals by the same type of indicators R0,max or R0,r with the coals of Australia, USA, Canada, Poland, Germany, the equations of the relationship between the average maximum (R0,max) and the average arbitrary (R0,r) vitrinite reflectance presented for the coals of these countries according to publications in scientific journals.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.673
Threshold uncertainty score0.680

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.037
GPT teacher head0.262
Teacher spread0.225 · 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 designNot applicable
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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueFerrous Metallurgy Bulletin of Scientific Technical and Economic InformationSame topicCoal and Coke Industries ResearchFrench-language works237,207