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Record W2951020251 · doi:10.32014/2019.2518-170x.85

NANOENERGETIC MATERIALS AND LOW-CARBON NANOENERGETICS: REGULARITIES, TECHNOLOGY AND RAW PRODUCTS

2018· article· en· W2951020251 on OpenAlexaff
Abulkhair Kairatovich Abzhaliyev

Bibliographic record

VenueNEWS of National Academy of Sciences of the Republic of Kazakhstan · 2018
Typearticle
Languageen
FieldEngineering
TopicMining and Gasification Technologies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCitationInclusion (mineral)Index (typography)Quality (philosophy)Raw materialScience Citation IndexLibrary scienceComputer scienceEngineeringWorld Wide WebSociologyChemistrySocial sciencePhysics

Abstract

fetched live from OpenAlex

The quality and depth of content Web of Science offers to researchers, authors, publishers, and institutions sets it apart from other research databases. The inclusion of News of NAS RK. Series of geology and technical sciences in the Emerging Sources Citation Index demonstrates our dedication to providing the most relevant and influential content of geology and engineering sciences to our community.Қазақстан Республикасы Ұлттық ғылым академиясы "ҚР ҰҒА Хабарлары.Геология жəне техникалық ғылымдар сериясы" ғылыми журналының

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0100.029
Science and technology studies0.0010.001
Scholarly communication0.0050.005
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.245
Teacher spread0.226 · 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 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

Citations3
Published2018
Admission routes1
Has abstractyes

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Same venueNEWS of National Academy of Sciences of the Republic of KazakhstanSame topicMining and Gasification TechnologiesFrench-language works237,207