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Record W2885538127 · doi:10.1038/s41467-018-05736-x

Distributed natural gas venting offshore along the Cascadia margin

2018· article· en· W2885538127 on OpenAlexaff
Michael Riedel, Martin Scherwath, Miriam Römer, M. Veloso, M. Heesemann, G. D. Spence

Bibliographic record

VenueNature Communications · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsOcean Networks Canada SocietyUniversity of Victoria
FundersNational Oceanic and Atmospheric Administration
KeywordsMethaneGeologySubmarine pipelineMargin (machine learning)OutflowNormalization (sociology)Continental marginFlareFlux (metallurgy)SeismologyOceanographyPhysicsMaterials scienceChemistry

Abstract

fetched live from OpenAlex

Abstract Widespread gas venting along the Cascadia margin is investigated from acoustic water column data and reveals a nonuniform regional distribution of over 1100 mapped acoustic flares. The highest number of flares occurs on the shelf, and the highest flare density is seen around the nutrition-rich outflow of the Juan de Fuca Strait. We determine ∼430 flow-rates at ∼340 individual flare locations along the margin with instantaneous in situ values ranging from ∼6 mL min −1 to ∼18 L min −1 . Applying a tidal-modulation model, a depth-dependent methane density, and extrapolating these results across the margin using two normalization techniques yields a combined average in situ flow-rate of ∼88 × 10 6 kg y −1 . The average methane flux-rate for the Cascadia margin is thus estimated to ∼0.9 g y −1 m −2 . Combined uncertainties result in a range of these values between 4.5 and 1800% of the estimated mean values.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.264
Teacher spread0.251 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations78
Published2018
Admission routes1
Has abstractyes

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