MétaCan
Menu
Back to cohort

Acidophilic microbial communities associated with a natural, biodegraded hydrocarbon seepage

2006· article· en· W2090892571 on OpenAlexafffund
Wilfred F. M. Röling, S. Ortega-Lucach, Steve Larter, Ian M. Head

Bibliographic record

VenueJournal of Applied Microbiology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTemperature gradient gel electrophoresisMicrobial population biologyBiodegradationPetroleumBioremediationAlphaproteobacteriaArchaeaEnvironmental chemistryBacteriaBiologyGammaproteobacteriaMetagenomicsMicrobial ecologyDominance (genetics)MicroorganismEcologyChemistry16S ribosomal RNABiochemistryGene

Abstract

fetched live from OpenAlex

Characterization of microbial communities present in a surface petroleum seep in which hydrocarbons have been biodegraded for thousands of years in order to improve the understanding on natural petroleum biodegradation. DNA was extracted from a natural, surface petroleum seep and subjected to culture independent analysis (rRNA gene-based denaturing gradient gel electrophoresis and phylogenetic analysis of clone libraries). Molecular analysis suggested dominance by acidophilic bacteria, especially Alphaproteobacteria (mainly bacteria related to Acidiphilium and Acidocella). Archaea were not detected, but fungi were present. pH of the samples was around 3.5. Acidophilic microbial communities are associated with an acidic petroleum seep. Microbial community structure analysis gives information on the environmental conditions under which petroleum biodegradation occurs. This knowledge could be applied to define conditions for specific cultivation or activity measurements. The activity of acidophilic micro-organisms deserves more attention with respect to their involvement in natural petroleum degradation. This knowledge will contribute to the design of oil bioremediation strategies for polluted acidic settings.

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 score0.082
Threshold uncertainty score0.659

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 head0.005
GPT teacher head0.171
Teacher spread0.166 · 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

Citations41
Published2006
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Applied MicrobiologySame topicMicrobial bioremediation and biosurfactantsFrench-language works237,207