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Record W3203812565 · doi:10.18280/i2m.200407

Sniffer: A Device for Sampling Gases from River

2021· article· en· W3203812565 on OpenAlexvenueno aff
Jonathan Gervaix, Pascal Breil, Franck Poly, Philippe Namour

Bibliographic record

VenueInstrumentation Mesure Métrologie · 2021
Typearticle
Languageen
FieldChemical Engineering
TopicOdor and Emission Control Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceGreenhouse gasSpring (device)Hydrology (agriculture)SedimentSampling (signal processing)STREAMSEnvironmental engineeringGeologyOceanographyEngineeringTelecommunications

Abstract

fetched live from OpenAlex

Description and validation of a new simple, inexpensive iso-pressure device for quantitative measurements of gas emissions in river (the SNIFFER for "Sampler of Natural InFluxes of Foul Emissions from River sediment"). The Sniffer was validated, during two field campaigns, a first in winter (18/12/13 to 20/02/14) and a second in spring (16/04/14 to 14/05/14) on a stream receiving some organic matter from a combined sewer overflow. The measured CH4 emissions are of the order of 0.50 L/(m2.day). This production is far from negligible and commits us to reconsider the contribution of water systems in total greenhouse gas emissions.

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)0.001
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 score0.109
Threshold uncertainty score0.635

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.060
GPT teacher head0.322
Teacher spread0.262 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2021
Admission routes1
Has abstractyes

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