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Record W2476020643 · doi:10.1002/srin.200300196

Investigation of Waste Wood as a Blast Furnace Injectant

2003· article· en· W2476020643 on OpenAlexaff
Masashi Takekawa, Kazumasa Wakimoto, M. Matsuura, M. Hasegawa, M. Iwase, Alex McLean

Bibliographic record

Venuesteel research international · 2003
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsUniversity of Toronto
Fundersnot available
Keywordstar (computing)CharBlast furnaceDecompositionBlast furnace gasWaste managementMaterials scienceInduction furnaceCypressBiomass (ecology)Gas phasePyrolysisEnvironmental scienceMetallurgyChemistryEngineeringGeology

Abstract

fetched live from OpenAlex

National legislation within Japan has increased the need for the development of new process technologies that will utilize waste wood materials. In order to generate some fundamental data with respect to the possible injection of such materials into blast furnaces, a study has been made of the decomposition and gasification reactions that take place when biomass material, in this case Japanese cypress chips, are exposed to temperatures between 1673 and 2073K using a high frequency induction furnace. The relative amounts of gas, char and tar were determined as well as the concentration of the various species present in the gas phase. The results obtained from gas analysis were in good agreement with values calculated from thermodynamic equilibria.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.954

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)0.0010.000

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 head0.040
GPT teacher head0.302
Teacher spread0.262 · 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

Citations17
Published2003
Admission routes1
Has abstractyes

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