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Record W1996809682 · doi:10.1002/clen.200700213

An Overview of the Biochemical and Molecular Aspects of Microbial Oxidation of Inorganic Sulfur Compounds

2008· article· en· W1996809682 on OpenAlex
Bidyut R. Mohapatra, W. Douglas Gould, O. Dinardo, David W. Koren

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

VenueCLEAN - Soil Air Water · 2008
Typearticle
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsSulfurMicroorganismSulfur metabolismArchaeaChemistryMicrobial metabolismBioremediationBacteriaCatalysisSulfateContext (archaeology)Environmental chemistryBiochemistryOrganic chemistryBiology

Abstract

fetched live from OpenAlex

Abstract Inorganic sulfur compounds are oxidized mostly to sulfate by microorganisms belonging to the bacteria and archaea domains. These microorganisms produce different types of enzymes, e. g., oxidoreductases and hydrolases for the metabolism of inorganic sulfur compounds. These versatile biocatalysts have potential biotechnological applications in different fields including biohydrometallurgical processes for recovering precious heavy metals and also for bioremediation of sulfides in industrial waste effluents. Appropriate knowledge on the enzymatic pathways of inorganic sulfur compounds oxidation will help to tailor the catalytic properties of these microorganisms so that they are optimal not only for a given reaction but also in the context of harsh industrial processes. This review describes the distribution of inorganic sulfur compound‐oxidizing microorganisms, various enzymatic systems associated with sulfur metabolism, and identification of the gene(s) responsible for catalysis of different enzymatic reactions.

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 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 score0.008
Threshold uncertainty score0.182

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 head0.018
GPT teacher head0.225
Teacher spread0.207 · 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