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Effects of Low Temperature and Freeze-Thaw Cycles on Hydrocarbon Biodegradation in Arctic Tundra Soil

2001· article· en· W2106760880 on OpenAlexafffund
Mikael Eriksson, Jong-Ok Ka, William W. Mohn

Bibliographic record

VenueApplied and Environmental Microbiology · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiodegradationMicrocosmHydrocarbonTundraMineralization (soil science)Environmental chemistryIncubationCarbon dioxideTotal petroleum hydrocarbonRibosomal Intergenic Spacer analysisChemistryHeterotrophSoil contaminationEcologyContaminationBacteriaBiologyArcticRibosomal RNAOrganic chemistryBiochemistryNitrogen

Abstract

fetched live from OpenAlex

Degradation of petroleum hydrocarbons was monitored in microcosms with diesel fuel-contaminated Arctic tundra soil incubated for 48 days at low temperatures (-5, 0, and 7 degrees C). An additional treatment was incubation for alternating 24-h periods at 7 and -5 degrees C. Hydrocarbons were biodegraded at or above 0 degrees C, and freeze-thaw cycles may have actually stimulated hydrocarbon biodegradation. Total petroleum hydrocarbon (TPH) removal over 48 days in the 7, 0, and 7 and -5 degrees C treatments, respectively, was 450, 300, and 600 microg/g of soil. No TPH removal was observed at -5 degrees C. Total carbon dioxide production suggested that TPH removal was due to biological mineralization. Bacterial metabolic activity, indicated by RNA/DNA ratios, was higher in the middle of the experiment (day 21) than at the start, in agreement with measured hydrocarbon removal and carbon dioxide production activities. The total numbers of culturable heterotrophs and of hydrocarbon degraders did not change significantly over the 48 days of incubation in any of the treatments. At the end of the experiment, bacterial community structure, evaluated by ribosomal intergenic spacer length analysis, was very similar in all of the treatments but the alternating 7 and -5 degrees C treatment.

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)0.000
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 score0.332
Threshold uncertainty score0.568

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 head0.156
Teacher spread0.154 · 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.

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

Citations152
Published2001
Admission routes2
Has abstractyes

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