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Record W2246678048 · doi:10.1021/acs.est.5b03251

From Spill to Sequestration: The Molecular Journey of Contamination via Comprehensive Multiphase NMR

2015· article· en· W2246678048 on OpenAlexafffund
Hussain Masoom, Denis Courtier‐Murias, Ronald Soong, Werner Maas, Michael Fey, Rajeev Kumar, Martine Monette, Henry J. Stronks, Myrna J. Simpson, André J. Simpson

Bibliographic record

VenueEnvironmental Science & Technology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicPer- and polyfluoroalkyl substances research
Canadian institutionsBruker (Canada)University of Toronto
FundersUniversity of Toronto ScarboroughOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Research, Innovation and ScienceKrembil FoundationCanada Foundation for Innovation
KeywordsPerfluorooctanoic acidChemistryLigninEnvironmental chemistryContaminationSoil waterSorptionPhase (matter)Soil contaminationChemical engineeringAdsorptionSoil scienceOrganic chemistryEnvironmental science

Abstract

fetched live from OpenAlex

Comprehensive multiphase NMR is a novel NMR technique that permits all components (solutions, gels, and solids) to be studied in unaltered natural samples. In this study a wide range of CMP-NMR interaction and editing-based experiments are combined to follow contaminants (pentafluorophenol (PFP) and perfluorooctanoic acid (PFOA)) from the solution state (after a spill) through the gel-state and finally into the true solid-state (sequestered) in an intact water-swollen soil. Kinetics experiments monitoring each phase illustrate PFOA rapidly transfers from solution to the solid phase while for PFP the process is slower with longer residence times in the solution and gel phase. Interaction-based experiments reveal that PFOA enters the soil via its hydrophobic tails and selectively binds to soil microbial protein. PFP sorption shows less specificity exhibiting interactions with a range of gel and solid soil components with a preference toward aromatics (mainly lignin). The results indicate that in addition to more traditional measurements such as Koc, other factors including the influence of the contaminant on the soil-water interface, specific biological interactions, soil composition (content of lignin, protein, etc.) and physical accessibility/swellability of soil organic components will likely be central to better explaining and predicting the true behavior of contaminants in 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0000.001
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 head0.022
GPT teacher head0.289
Teacher spread0.267 · 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 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

Citations37
Published2015
Admission routes2
Has abstractyes

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