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How G.N. Lewis Reset the Terms of the Dialogue between Chemistry and Physics

2003· article· en· W2009860499 on OpenAlexaff
Paul Bogaard

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2003
Typearticle
Languageen
FieldChemistry
TopicHistory and advancements in chemistry
Canadian institutionsMount Allison University
Fundersnot available
KeywordsValencyValence (chemistry)Bohr modelChemistryLewis acids and basesComputational chemistryTheoretical physicsValence bond theoryQuantum chemistryQuantum mechanicsChemical bondPhysicsMoleculePhilosophyOrganic chemistry

Abstract

fetched live from OpenAlex

While quantum physics provided a mathematical framework for understanding the valency of chemical elements, to make use of these mathematical equations required approximations based on chemical experience. To better understand how this establishes limits to the presumption that chemistry can be derived from physics, this paper starts with the warnings in Coulson's widely read text, Valence, as to why there are pitfalls in the interpretation of what "valence" accomplishes. He directs some of these concerns back to Pauling's earlier text, The Nature of the Chemical Bond. Both Coulson and Pauling are aware that quantum theory's ability to approximate the energetic stability of chemical systems is of use to chemistry only if it can be correlated with the molecular structure that results from chemical bonding. While this may now be routinely expected, it was a struggle to see that this was the challenge chemistry posed to physics-and this achievement they both attribute to G.N. Lewis. Until the more mature forms of quantum mechanics arose in the 1920s, Lewis was skeptical that the dynamic models of the atom posed by Bohr could meet this challenge. How Lewis formulates this challenge initially in 1916 and then in his longer work, Valence and the Structure of Atoms and Molecules, will be examined.

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.997
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.011
Scholarly communication0.0060.011
Open science0.0010.002
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0030.002

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 head0.095
GPT teacher head0.319
Teacher spread0.224 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations3
Published2003
Admission routes1
Has abstractyes

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