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Record W2981839501 · doi:10.1002/ceat.201900404

Effect of Substrate Characteristics and Process Fluid Percolation on Dry Anaerobic Digestion Processes

2019· article· en· W2981839501 on OpenAlex
Harald Wedwitschka, Daniela Gallegos, Michael Tietze, J. Reinhold, Earl Jenson, Jan Liebetrau, Michael Nelles

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

VenueChemical Engineering & Technology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsAlberta Medical Association
FundersBundesministerium für Wirtschaft und Energie
KeywordsAnaerobic digestionCompactionMethaneMaterials sciencePercolation (cognitive psychology)Permeability (electromagnetism)Pulp and paper industryChemistryWaste managementChemical engineeringComposite materialOrganic chemistryEngineeringBiochemistry

Abstract

fetched live from OpenAlex

Abstract The dry anaerobic batch digestion process is an organic waste treatment technology most appropriate for the treatment of stackable (non‐free‐flowing) dry organic waste materials. The effect of the process fluid percolation and substrate permeability on methane production of organic household waste was investigated in anaerobic dry digestion trials at pilot scale. The container system consisted of two percolation digesters and a fixed‐bed methane digester. The experimental results indicate that material compaction occurs during the digestion process and can have a negative effect on substrate permeability. Structure material addition reduced material compaction and as a result increased the substrate permeability.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.480

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.002
GPT teacher head0.190
Teacher spread0.188 · 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