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Record W2282215901

Biochemical methane potential (BMP) of solid organic materials: results obtained from an international interlaboratory study

2010· preprint· en· W2282215901 on OpenAlexaff
F. Raposo, V. Fernández‐Cegrí, M.A. de la Rubia, R. Borja, Fabrice Béline, Cristina Cavınato, Göksel N. Demirer, J.C. Fernández, Jean‐Claude Frigon, J. Koubova, R. Méndez, G. Menin, A. Peene, Paul Scherer, M. Torrijos, G. Rangarej, Hinrich Uellendahl, Isabella Wierinck, Vinnie de Wilde

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2010
Typepreprint
Languageen
FieldMedicine
TopicRenal function and acid-base balance
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMethaneBiochemical engineeringEnvironmental chemistryEnvironmental scienceChemistryProcess engineeringComputer scienceEngineeringOrganic chemistry
DOInot available

Abstract

fetched live from OpenAlex

This paper describes the results obtained for different participating research groups in an interlaboratory study related to the biochemical methane potential (BMP). In this research work, the full experimental conditions influencing the test such as inoculum, substrate characteristics and experimental conditions were reported. The study was performed using 4 samples: 3 reference substrates (starch, cellulose and gelatine), and 1 raw material (mung bean). The BMP of mung bean was carried out at two inoculum to substrate ratios (ISR), specifically 2 and 1. The methane yields of reference substrates for starch, cellulose and gelatine were 352±33, 353±29 and 382±42 mL/g VSadded, respectively. The percentages of biotransformation of these substrates into methane were 85±8, 85±7 and 88±10%, respectively. On the other hand, the values of methane yields and biodegradability for MB were 373±35 mL CH4/g VSadded and 86±8%, respectively. In addition, the anaerobic digestion of the raw material elected did not show influence on the ISR in the extent of the biotransformation.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.010
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.012
GPT teacher head0.273
Teacher spread0.260 · 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.

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

Citations1
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueHAL (Le Centre pour la Communication Scientifique Directe)Same topicRenal function and acid-base balanceFrench-language works237,207