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Possible roles of reactive chlorine II: assessing biotic chlorination as a way for organisms to handle oxygen stress

2012· review· en· W1734096959 on OpenAlexafffund
Per Bengtson, David Bastviken, Gunilla Öberg

Bibliographic record

VenueEnvironmental Microbiology · 2012
Typereview
Languageen
FieldChemistry
TopicVanadium and Halogenation Chemistry
Canadian institutionsUniversity of British Columbia
FundersLuonnontieteiden ja Tekniikan Tutkimuksen ToimikuntaNatural Sciences and Engineering Research Council of CanadaVetenskapsrådet
KeywordsChlorineOrganic matterMicroorganismReactive oxygen speciesBiologyEnvironmental chemistryOxygenOrganismBacteriaEcologyChemistryBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Natural formation of organically bound chlorine is extensive in many environments. The enzymes associated with the formation of chlorinated organic matter are produced by a large variety of organisms. Little is known about the ecological role of the process, the key question being: why do microorganisms promote chlorination of organic matter? In a recent paper we discuss whether organic matter chlorination may be a result of antagonistic interactions among microorganisms. In the present paper we evaluate whether extracellular microbial formation of reactive chlorine may be used as a defence against oxygen stress, and we discuss whether this process is likely to contribute to the formation of chlorinated organic matter. Our analysis suggests that periodic exposure to elevated concentrations of reactive oxygen species is a common denominator among the multitude of organisms that are able to enzymatically catalyse formation of reactive chlorine. There is also some evidence suggesting that the production of such enzymes in algae and bacteria is induced by oxygen stress. The relative contribution from this process to the extensive formation of chlorinated organic matter in natural environments remains to be empirically assessed.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.481
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.280
Teacher spread0.256 · 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.

Study designBench or experimental
Domainnot available
GenreReview

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

Citations27
Published2012
Admission routes2
Has abstractyes

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