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Record W2495928935 · doi:10.2136/sssabookser5.4.c44

4.2 Gas Sampling and Analysis

2002· book-chapter· en· W2495928935 on OpenAlexaff
R. Farrell, Eeltje de Jong, Jane A. Elliott

Bibliographic record

VenueSoil Science Society of America book series · 2002
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsEnvironment and Climate Change CanadaUniversity of Saskatchewan
Fundersnot available
KeywordsDetectorThermal conductivity detectorIonizationAerationHelium ionization detectorHeliumAnalytical Chemistry (journal)Materials scienceFlame ionization detectorDischarge ionization detectorChemistryEnvironmental sciencePhysicsOpticsAtomic physicsEnvironmental chemistryGas chromatographyChromatographyIon

Abstract

fetched live from OpenAlex

Evaluation of the aeration status of a soil at the soil–air or soil–water interface provides an excellent opportunity to assess the influence of aeration on plant growth and microbial processes. Van Bavel described one of the first field-based analytical systems for the in situ determination of oxygen and carbon dioxide in soil. The thermal conductivity detector (TCD) and HID, ultrasonic detectors are considered universal detectors because they respond to all gases. The helium ionization detector (HID) measures the increase in electrical conductivity resulting from the ionization of gases in the sample gas stream caused by collision with metastable helium atoms. The flame photometric detector (FPD) employs either a monochrometer or filter system to isolate the emission wavelength of a particular element, thus making this detector highly selective. As with the electron capture detector, the response of the FPD is inherently nonlinear, though the signal may be electronically linearized over a narrow concentration range.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.019
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0190.013

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 head0.012
GPT teacher head0.213
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

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 designNot applicable
Domainnot available
GenreMethods

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

Citations6
Published2002
Admission routes1
Has abstractyes

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