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Record W6981688389

Examining microbial carbon source cycling in arsenic contaminated Bangladesh aquifers through lipid and isotopic analyses

2017· dissertation· en· W6981688389 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.

fundA Canadian funder is recorded on the work.
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

VenueMacSphere (McMaster University) · 2017
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicColor Science and Applications
Canadian institutionsnot available
FundersNational Institute of Environmental Health SciencesNatural Sciences and Engineering Research Council of Canada
KeywordsAquiferOrganic matterArsenicGroundwaterSedimentary organic matterMicrobial population biologyTotal organic carbonCarbon cycle
DOInot available

Abstract

fetched live from OpenAlex

Understanding how organic matter is microbially cycled through Bangladesh aquifers is a key component in understanding the spatial and temporal patterns of arsenic release into groundwater occurring on wide regional scales. There is a current gap in the literature for how overall microbial carbon cycles are functioning in Bangladesh aquifers, how these microbial metabolisms factor into arsenic release, including methodology as to approach these questions in situ. This research aimed to provide insight into carbon sources and cycling of the microbial communities in Bangladesh aquifers through a complimentary applied suite of lipidomic, isotopic and inorganic analytical approaches on in situ sediments and groundwater from Bangladesh aquifers. Through radiocarbon analyses of phospholipid fatty acids (PLFA's), bacterial populations in a shallow Holocene-aged and high arsenic aquifer were found to be predominantly utilizing younger organic matter as their carbon source rather than older sedimentary carbon. At the sites studied, the sources of younger organic matter that coincide with zones where increased reductive dissolution of iron and arsenic release is occurring were consistent with human and livestock waste identified through sedimentary sterol distributions (phytosterols and coprstonaol) and Cl/Br mass ratios in groundwater. Since poor sanitation is widespread across Bangladesh, sewage-derived waste should be considered a prevalent potential microbial carbon source is these systems. An examination of sediment- versus groundwater-associated microbial communities in Bangladesh aquifers (through PLFA analysis) suggested that the former is 5-6 orders of magnitude more abundant than the latter. Archaeal communities, examined through both groundwater methane and sedimentary archaeal lipid (archaeol and glycerol dialkyl glycerol tetraether (GDGT)) analysis, are suggested to be highly active (depths 5-240 m) but to varying degrees in Bangladesh aquifers. Methanogenesis, dominantly being carried out through CO2 reduction, appears to be spatially associated at some sites with zones of iron/arsenic reductive dissolution in the Bangladesh aquifers. The analytical approaches and conceptual frameworks applied throughout this dissertation have been demonstrated to be effective strategies to understand how microbial carbon cycling is occurring at a community level and intimately involved in arsenic release.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.817
Threshold uncertainty score1.000

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)0.0030.000

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 head0.030
GPT teacher head0.266
Teacher spread0.236 · 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