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Record W2401059805 · doi:10.1139/cjce-2015-0279

Maximum acceptable concentration levels of the chemical agent sarin in Canadian and Russian soil types

2016· article· en· W2401059805 on OpenAlexafffundvenueabout
Alexander A. Maslennikov, Boris N. Filatov, Svetlana Demidova, P. Samuleev, Katherine A. M. Creber, William S. Andrews

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicPesticide and Herbicide Environmental Studies
Canadian institutionsRoyal Military College of Canada
FundersGovernment of Canada
KeywordsSarinSoil waterEnvironmental scienceEnvironmental chemistrySoil testAnimal scienceToxicologyChemistrySoil scienceBiology

Abstract

fetched live from OpenAlex

The lowest-observed-adverse-effect and no-observed-adverse-effect concentrations of sarin were determined in soils typical to Canada and Russia. Maximum acceptable concentrations were established to be 3.0 × 10−4 mg kg−1 for the standard reference soil, 2.0 × 10−3 mg kg−1 for prairie soil, and 1.0 × 10−2 mg kg−1 for forest soil.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.501
Threshold uncertainty score0.992

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.008
GPT teacher head0.177
Teacher spread0.169 · 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

Citations1
Published2016
Admission routes4
Has abstractyes

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Same venueCanadian Journal of Civil EngineeringSame topicPesticide and Herbicide Environmental StudiesFrench-language works237,207