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Record W2129754946 · doi:10.1029/2004gl021359

Evidence for microbial enhanced electrical conductivity in hydrocarbon‐contaminated sediments

2004· article· en· W2129754946 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGeophysical Research Letters · 2004
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMicrobial population biologyEnvironmental chemistryWater columnContaminationWeatheringConductivityPopulationMicroorganismEnvironmental scienceGeologyMineralogySoil scienceChemistryEcologyBiologyGeochemistryOceanographyBacteria

Abstract

fetched live from OpenAlex

Bulk electrical conductivity of sediments during microbial mineralization of diesel was investigated in a mesoscale laboratory experiment consisting of biotic contaminated and uncontaminated columns. Population numbers of oil degrading microorganisms increased with a clear pattern of depth zonation within the contaminated column not observed in the uncontaminated column. Microbial community structure determined from ribosomal DNA intergenic spacer analysis showed a highly specialized microbial community in the contaminated column. The contaminated column showed temporal increases in bulk conductivity, dissolved inorganic carbon, and calcium, suggesting that the high bulk conductivity is due to enhanced mineral weathering from microbial activity. The greatest change in bulk conductivity occurred in sediments above the water table saturated with diesel. Variations in electrical conductivity magnitude and microbial populations and their depth distribution in the contaminated column are similar to field observations. The results of this study suggest that geophysical methodologies may potentially be used to investigate microbial activity.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.685
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.082
GPT teacher head0.353
Teacher spread0.271 · 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