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A Comprehensive Exploration of Biomass Gasification Technologies Advancing United Nations Sustainable Development Goals: Part II

2024· article· en· W4404228803 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJohnson Matthey Technology Review · 2024
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsBiomass (ecology)Sustainable developmentBiomass gasificationEnvironmental scienceNatural resource economicsPolitical scienceEconomicsGeologyOceanography

Abstract

fetched live from OpenAlex

Part II of this review focuses on methodologies and protocols employed in biomass gasification, recognising its pivotal role in sustainable energy generation. Additionally, the article discusses the challenges associated with gasification technology, such as tar formation, biomass heterogeneity and uneven biomass supply in different seasons. It emphasises the need for further research and infrastructure development to overcome these barriers and facilitate the efficient distribution and commercialisation of biomass gasification technology. Overall, the scope of the article extends to providing insights into the status, challenges and future prospects of biomass gasification for achieving sustainable energy goals.

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.

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: Review · Consensus signal: none
Teacher disagreement score0.582
Threshold uncertainty score0.834

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.007
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 head0.023
GPT teacher head0.264
Teacher spread0.242 · 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