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Record W1973453770 · doi:10.4236/jep.2012.312181

Prokaryotic Horizontal Gene Transfer in Freshwater Lakes: Implications of Dynamic Biogeochemical Zonation

2012· article· en· W1973453770 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

VenueJournal of Environmental Protection · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBiogeochemical cycleHorizontal gene transferFreshwater ecosystemEcologyBiologyEcosystemGenePhylogeneticsGenetics

Abstract

fetched live from OpenAlex

The highly adaptive nature of prokaryotic communities in the face of changing environmental conditions reflects in part their ability to share advantageous genetic information through horizontal gene transfer (HGT). Natural freshwater lacustrine (lake) systems are a vital and finite resource, and the influence of HGT on their quality (e.g. enabling the spread of antibiotic resistance and xenobiotic catabolism genes) is likely significant. Laboratory and in situ studies indicate that the dynamic physical, chemical, and biological conditions that structure freshwater systems can influence HGT within freshwater prokaryotic communities. Thus, understanding how biogeochemical parameters impact HGT in freshwater lakes is an emerging knowledge gap with potential implications for ecosystem and human health on a global scale. In this review, we provide a general synopsis of what is known about HGT in freshwater prokaryotic communities, followed by an integrated summary of current knowledge identifying how biogeochemical factors may influence prokaryotic HGT in freshwater lacustrine systems.

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 categoriesInsufficient payload (model declined to judge)
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 score0.747
Threshold uncertainty score0.999

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)0.0020.000

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 head0.010
GPT teacher head0.211
Teacher spread0.201 · 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