MétaCan
Menu
Back to cohort
Record W2124478607 · doi:10.1039/b705742c

Further links between the maximum hardness principle and the hard/soft acid/base principle: insights from hard/soft exchange reactions

2007· article· en· W2124478607 on OpenAlex
Pratim Kumar Chattaraj, Paul W. Ayers, Junia Melin

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.

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2007
Typearticle
Languageen
FieldChemistry
TopicCrystallography and molecular interactions
Canadian institutionsMcMaster University
Fundersnot available
KeywordsHSAB theoryBase (topology)Acid–base reactionContext (archaeology)ChemistryThermodynamicsSoft waterComputational chemistryMathematicsPhysicsPhysical chemistryOrganic chemistryMathematical analysis

Abstract

fetched live from OpenAlex

Ayers, Parr, and Pearson recently showed that insight into the hard/soft acid/base (HSAB) principle could be obtained by analyzing the energy of reactions in hard/soft exchange reactions, i.e., reactions in which a soft acid replaces a hard acid or a soft base replaces a hard base [J. Chem. Phys., 2006, 124, 194107]. We show, in accord with the maximum hardness principle, that the hardness increases for favorable hard/soft exchange reactions and decreases when the HSAB principle indicates that hard/soft exchange reactions are unfavorable. This extends the previous work of the authors, which treated only the "double hard/soft exchange" reaction [P. K. Chattaraj and P. W. Ayers, J. Chem. Phys., 2005, 123, 086101]. We also discuss two different approaches to computing the hardness of molecules from the hardness of the composing fragments, and explain how the results differ. In the present context, it seems that the arithmetic mean of fragment softnesses is the preferable definition.

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 categoriesMeta-epidemiology (narrow)
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 score0.068
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.019
GPT teacher head0.264
Teacher spread0.245 · 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