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Record W4319320794 · doi:10.1002/citp.202370104

Forschung und Entwicklung

2023· article· de· W4319320794 on OpenAlexaff
Guangyi Zhang, Andreas Bück

Bibliographic record

VenueCITplus · 2023
Typearticle
Languagede
FieldBusiness, Management and Accounting
TopicCorporate Governance and Management
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCitationComputer scienceLibrary scienceWorld Wide WebInformation retrieval

Abstract

fetched live from OpenAlex

Energierückgewinnung aus Ölschlamm-Kohle Die Pyrolyse von Ölschlämmen lässt sogenannte Ölschlamm-Kohle (OSC) zurück, eine Kohle mit hohem Aschegehalt.Aufgrund ihres hohen Metallgehalts zählt sie als Giftmüll und muss entsprechend entsorgt werden.Eine Alternative könnte eine umweltverträgliche Energierückgewinnung sein.In einer Studie wurde OSC in einem kontinuierlichen Wirbelschichtbrenner unter Zugabe von Braunkohle verbrannt.Braunkohle verbessert die Verbrennung, eine zu große Menge führt jedoch zu Verschlackung.Feine Kokspartikel im Ölschlamm und flüchtige Verbindungen in der Braunkohle sorgen für Temperaturstufen entlang des Fließbetts.In Kombination mit einer Luftstufung und einer selektiven nicht-katalytischen Reduktion ließen sich ausgezeichnete Verbrennungsleistungen und eine effiziente Reduktion von NOx erzielen.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.252
Threshold uncertainty score0.842

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0040.009
Science and technology studies0.0030.002
Scholarly communication0.0160.006
Open science0.0020.010
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.2520.295

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 head0.024
GPT teacher head0.240
Teacher spread0.216 · 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 designTheoretical or conceptual
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
Published2023
Admission routes1
Has abstractno

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