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Record W2087754972 · doi:10.1080/10934529.2014.910033

Prediction of the air-water partition coefficient for perfluoro-2-methyl-3-pentanone using high-level Gaussian-4 composite theoretical methods

2014· article· en· W2087754972 on OpenAlexaff
Sierra Rayne, Kaya Forest

Bibliographic record

VenueJournal of Environmental Science and Health Part A · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicPer- and polyfluoroalkyl substances research
Canadian institutionsSaskatchewan Polytechnic
Fundersnot available
KeywordsSolvationChemistryAqueous solutionHydratePartition coefficientAtmosphere (unit)CalibrationActivity coefficientAnalytical Chemistry (journal)ThermodynamicsMathematicsChromatographyMoleculePhysical chemistryPhysicsOrganic chemistryStatistics

Abstract

fetched live from OpenAlex

The air-water partition coefficient (Kaw) of perfluoro-2-methyl-3-pentanone (PFMP) was estimated using the G4MP2/G4 levels of theory and the SMD solvation model. A suite of 31 fluorinated compounds was employed to calibrate the theoretical method. Excellent agreement between experimental and directly calculated Kaw values was obtained for the calibration compounds. The PCM solvation model was found to yield unsatisfactory Kaw estimates for fluorinated compounds at both levels of theory. The HENRYWIN Kaw estimation program also exhibited poor Kaw prediction performance on the training set. Based on the resulting regression equation for the calibration compounds, the G4MP2-SMD method constrained the estimated Kaw of PFMP to the range 5-8 × 10(-6) M atm(-1). The magnitude of this Kaw range indicates almost all PFMP released into the atmosphere or near the land-atmosphere interface will reside in the gas phase, with only minor quantities dissolved in the aqueous phase as the parent compound and/or its hydrate/hydrate conjugate base. Following discharge into aqueous systems not at equilibrium with the atmosphere, significant quantities of PFMP will be present as the dissolved parent compound and/or its hydrate/hydrate conjugate base.

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)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score0.788

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.067
GPT teacher head0.359
Teacher spread0.292 · 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 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

Citations6
Published2014
Admission routes1
Has abstractyes

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Same venueJournal of Environmental Science and Health Part ASame topicPer- and polyfluoroalkyl substances researchFrench-language works237,207