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Molecular characterization of methanotrophic communities in forest soils that consume atmospheric methane

2007· article· en· W1793617181 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

VenueFEMS Microbiology Ecology · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial metabolism and enzyme function
Canadian institutionsUniversity of British Columbia
FundersNational Science Foundation
KeywordsMethanotrophBiologyAlphaproteobacteriaSoil waterMethane monooxygenase16S ribosomal RNAAnaerobic oxidation of methaneAtmospheric methaneSoil microbiologyMethaneAbundance (ecology)EcologyBotanyBacteriaGenetics

Abstract

fetched live from OpenAlex

Methanotroph abundance was analyzed in control and long-term nitrogen-amended pine and hardwood soils using rRNA-targeted quantitative hybridization. Family-specific 16S rRNA and pmoA/amoA genes were analyzed via PCR-directed assays to elucidate methanotrophic bacteria inhabiting soils undergoing atmospheric methane consumption. Quantitative hybridizations suggested methanotrophs related to the family Methylocystaceae were one order of magnitude more abundant than Methyloccocaceae and more sensitive to nitrogen-addition in pine soils. 16S rRNA gene phylotypes related to known Methylocystaceae and acidophilic methanotrophs and pmoA/amoA gene sequences, including three related to the upland soil cluster Alphaproteobacteria (USCalpha) group, were detected across different treatments and soil depths. Our results suggest that methanotrophic members of the Methylocystaceae and Beijerinckiaceae may be the candidates for soil atmospheric methane consumption.

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)0.000
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 score0.065
Threshold uncertainty score0.954

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0010.000
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 head0.010
GPT teacher head0.221
Teacher spread0.211 · 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