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Record W3204329404 · doi:10.18280/i2m.200406

Innovative Instrument for the Field Continuous Monitoring of Dissolved Gases in Environmental Studies

2021· article· en· W3204329404 on OpenAlexvenueno aff
Eliot Chatton, Thierry Labasque, Aurélie Guillou, Paul Floury, Luc Aquilina, Virginie Vergnaud

Bibliographic record

VenueInstrumentation Mesure Métrologie · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality Monitoring and Analysis
Canadian institutionsnot available
FundersAgence Nationale de la Recherche
KeywordsBiogeochemical cycleEnvironmental scienceNoble gasChemistrySolubilityEnvironmental chemistryDissolved organic carbon

Abstract

fetched live from OpenAlex

Dissolved gases are particularly relevant tools for the investigation of environmental processes. Indeed, their solubility being a function of the variables of physical state of the medium (temperature, pressure, salinity), the dissolved noble gases are for instance good indicators of equilibrium conditions with the atmosphere and mixing of water bodies. Dissolved gases can also inform the biogeochemical functioning of natural systems by providing information on major processes such as photosynthesis, respiration or denitrification. Classical methods relying on the sampling, the storage and the ex situ analysis of water samples for the measurement of dissolved gases suffer from the difficulty of taking sufficiently frequent and representative samples as well as the analyte preservation. High-frequency in situ measurement of dissolved gases is therefore the most relevant for the study of environmental processes. The use of Membrane Inlet Mass Spectrometer (MIMS) technology provides access to high frequency measurements of a large set of dissolved gases in the field (He, Ne, Ar, Kr, Xe, N2, O2, CO2, CH4, N2O, H2) which offers a real opportunity for environmental studies.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.500
Threshold uncertainty score0.401

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 head0.057
GPT teacher head0.339
Teacher spread0.282 · 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 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

Citations1
Published2021
Admission routes1
Has abstractyes

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