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Record W2019904432 · doi:10.1021/ci049707l

Theoretical Derivation of Heuristic Molecular Lipophilicity Potential:  A Quantum Chemical Description for Molecular Solvation

2005· article· en· W2019904432 on OpenAlexaff
Qi-Shi Du, Pengjun Liu, Paul G. Mezey

Bibliographic record

VenueJournal of Chemical Information and Modeling · 2005
Typearticle
Languageen
FieldChemistry
TopicFree Radicals and Antioxidants
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsLipophilicitySolvationChemistryMolecular dynamicsComputational chemistryChemical physicsMoleculeDipoleImplicit solvationOrganic chemistry

Abstract

fetched live from OpenAlex

We present the theoretical derivation of a heuristic molecular lipophilicity potential (HMLP), which gives a structure-based and quantum chemical description of an important aspect of molecular solvation. The quantum mechanical electrostatic potential (ESP) V(r) on a formal molecular surface is calculated, and then the molecular lipophilicity potential L(r) is constructed by comparing the local electron density with the ESP on the surrounding atoms using a screening function. The screening function is derived from statistical mechanical theory treating the polar solvent molecules as dipoles. HMLP is able to describe the main interactions of solute molecules with polar and nonpolar solvent molecules. HMLP is a unified lipophilicity and hydrophilicity potential: its positive values represent lipophilicity, and its negative values represent hydrophilicity. In this paper, several examples show that HMLP gives more reliable descriptions for the molecular solvation than some other methods, such as atomic partial charges and the empirical lipophilicity potential.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.517
Threshold uncertainty score0.443

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 communication0.0000.001
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 head0.012
GPT teacher head0.239
Teacher spread0.227 · 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

Citations24
Published2005
Admission routes1
Has abstractyes

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