MétaCan
Menu
Back to cohort
Record W2065973992 · doi:10.1021/es034418j

Photochemical Alkylation of Inorganic Selenium in the Presence of Low Molecular Weight Organic Acids

2003· article· en· W2065973992 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnvironmental Science & Technology · 2003
Typearticle
Languageen
FieldNursing
TopicSelenium in Biological Systems
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsChemistrySeleniumAlkylationAlkylEnvironmental chemistryHydrideFormic acidOrganic chemistryPhotochemistryInorganic chemistryMetalCatalysis

Abstract

fetched live from OpenAlex

Using a flow-through photochemical reactor and a low pressure mercury lamp as a UV source, alkyl selenium species are formed from inorganic selenium(IV) in the presence of low molecular weight organic acids (LMW acids). The volatile alkyl Se species were cryogenically trapped and identified by GC-MS and GC-ICP-MS. In the presence of formic, acetic, propionic and malonic acids, inorganic selenium(IV) is converted by UV irradiation to volatile selenium hydride and carbonyl, dimethylselenide and diethylselenide, respectively. Se(IV) was successfully removed from contaminated agricultural drainage waters (California, U.S.A.) using a batch photoreactor system Se. Photochemical alkylation may thus offer a promising means of converting toxic selenium salts, present in contaminated water, to less toxic dimethylselenide. The LMW acids and photochemical alkylation process may also be key to understanding the source of atmospheric selenium and are likely involved in its mobility in the natural anaerobic environment.

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.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.771

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.005
GPT teacher head0.210
Teacher spread0.205 · 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