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Record W2338955548 · doi:10.3390/min6020036

Seasonal Microbial Population Shifts in a Bioremediation System Treating Metal and Sulfate-Rich Seepage

2016· article· en· W2338955548 on OpenAlexafffundabout
Susan A. Baldwin, Al Mattes, Maryam Rezadehbashi, Jon Taylor

Bibliographic record

VenueMinerals · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicMine drainage and remediation techniques
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaGenome British Columbia
KeywordsBioremediationBiosolidsPopulationSulfateOrganic matterEnvironmental chemistryMicroorganismEnvironmental scienceEcologyBiologyContaminationChemistryEnvironmental engineeringBacteria

Abstract

fetched live from OpenAlex

Biochemical reactors (BCRs) using complex organics for bioremediation of mine-influenced water must operate successfully year round. In cold climates, where many mines in Canada are located, survival of the important microorganisms through the winter months is a concern. In this work, broad phylogenetic surveys, using metagenomics, of the microbial populations in pulp mill biosolids used to remediate metal leachate containing As, Zn, Cd and sulfate were performed to see if the types of microorganisms present changed over the seasons of one year (August 2008 to July 2009). Despite temperature variations between 0 and 17 °C the overall structure of the microbial population was fairly consistent. A cyclical pattern in relative abundance was detected in certain taxa. These included fermenter-related groups, which were out of phase with other taxa such as Desulfobulbus that represented potential consumers of fermentation byproducts. Sulfate-reducers in the BCR biosolids were closely related to psychrotolerant species. Temperature was not a factor that shaped the microbial population structure within the BCR biosolids. Kinetics of organic matter degradation by these microbes and the rate of supply of organic carbon to sulfate-reducers would likely affect the metal removal rates at different temperatures.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 head0.218
Teacher spread0.210 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations22
Published2016
Admission routes3
Has abstractyes

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