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Record W4381513239 · doi:10.26434/chemrxiv-2023-5796t

Towards Universal Substituent Constants: Relating QTAIM Functional Group Descriptors to Substituent Effect Proxies

2023· preprint· en· W4381513239 on OpenAlexafffund
Kevin M. Lefrancois‐Gagnon, Robert C. Mawhinney

Bibliographic record

VenueChemRxiv · 2023
Typepreprint
Languageen
FieldComputer Science
TopicComputational Drug Discovery Methods
Canadian institutionsLakehead University
FundersAlliance de recherche numérique du CanadaLakehead University
KeywordsSubstituentTransferabilityChemistryLimitingLinear regressionSolvationMultivariate statisticsPrincipal component analysisComputational chemistryMathematicsMoleculeStereochemistryEconometricsStatisticsOrganic chemistry

Abstract

fetched live from OpenAlex

Substituents modulate reactions, but are commonly described using proxies to their true properties. Substituent descriptors from the Quantum Theory of Atoms in Molecules are related here to these proxies, which have historically had chemically intuitable effects. Due to the large number of descriptors, multivariate analysis is used to intuit their meaning. Multiple linear regression, Principal Components, and Partial Least Squares Regression analyses highlight that these substituent descriptors contain similar information to the proxies, while being truly substituent properties. Sources of error limiting quantitative reproduction of the proxies data include transferability, experimental accuracy, and solvation issues.

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)0.005
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.002
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.053
GPT teacher head0.293
Teacher spread0.240 · 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 designSimulation or modeling
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

Citations0
Published2023
Admission routes2
Has abstractyes

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