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Record W2038655315 · doi:10.1139/s02-037

A potential new role for fungi in a wastewater MBR biological nitrogen reduction system

2002· article· en· W2038655315 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsnot available
FundersUniversity of Tsukuba
KeywordsNitrificationDenitrificationWastewaterNutrientNitrifying bacteriaFastidious organismSewage treatmentBiologyBioreactorBacteriaEnvironmental chemistryNitrogenEnvironmental scienceEnvironmental engineeringEcologyChemistryBotany

Abstract

fetched live from OpenAlex

The fastidious nature of nitrifying bacteria has caused many operational problems for wastewater treatment plants employing some form of biological nutrient removal. Research in the field has focused solely on meeting the requirements of this group of bacteria. Recently fungi have been recognized to perform denitrification at greater rates than bacteria. Combining fungi nitrification ability and resistance to inhibitory chemicals, there is the potential for development of a new fungi based biological nitrogen removal system. From the data reviewed, the system would have several significant advantages over conventional biological nutrient removal systems. This paper reviews the ability of fungi to carry out biological nitrogen removal and the potential performance of a fungi based system. Key words: fungi, biological nutrient removal, nitrification, denitrification, membrane bioreactor.

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 score0.414
Threshold uncertainty score0.372

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 head0.008
GPT teacher head0.171
Teacher spread0.163 · 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