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Record W3196805525 · doi:10.3390/physchem1020015

Predicting 1,9-Decadiene−Water Partition Coefficients Using the 3D-RISM-KH Molecular Solvation Theory

2021· article· en· W3196805525 on OpenAlex
Dipankar Roy, Devjyoti Dutta, Andriy Kovalenko

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePhyschem · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpectroscopy and Quantum Chemical Studies
Canadian institutionsNational Institute for NanotechnologyUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSolvationPartition coefficientPartition (number theory)Liquid waterClosure (psychology)ThermodynamicsChemistryStatistical physicsPhysicsMathematicsMoleculeChromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

The Three-Dimensional Reference Interaction Site Model (3D-RISM) with Kovalenko−Hirata (KH) closure is applied to calculate the 1,9-Decadiene/Water partition coefficients for a diverse class of compounds. The liquid state of 1,9-Decadiene is represented with the united atom TraPPE force field parameters. The 3D-RISM-KH computed partition functions are in good agreement with the experimental results. Our computational scheme can be used for a quantitative structure partitioning prediction for decadiene-water system, which has been used in membrane-mimicking of the egg-lecithin/water permeability experiments.

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)0.000
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 score0.057
Threshold uncertainty score0.319

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.014
GPT teacher head0.265
Teacher spread0.251 · 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