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Preface

2003· book-chapter· en· W183445174 on OpenAlexaboutno aff
John M. Brown, Alan Carrington

Bibliographic record

VenueCambridge University Press eBooks · 2003
Typebook-chapter
Languageen
FieldChemistry
TopicMolecular Spectroscopy and Structure
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

A book whose title refers to the spectroscopy of diatomic molecules is, inevitably, going to be compared with the classic book written by G. Herzberg under the title Spectroscopy of Diatomic Molecules . This book was published in 1950, and it dealt almost entirely with electronic spectroscopy in the gas phase, studied by the classic spectrographic techniques employing photographic plates. The spectroscopic resolution at that time was limited to around 0.1 cm −1 by the Doppler effect; this meant that the vibrational and rotational structure of electronic absorption or emission band systems could be easily resolved in most systems. The diatomic molecules studied by 1950 included conventional closed shell systems, and a large number of open shell electronic states of molecules in both their ground and excited states. Herzberg presented a beautiful and detailed summary of the principles underlying the analysis of such spectra. The theory of the rotational levels of both closed and open shell diatomic molecules was already well developed by 1950, and the correlation of experimental and theoretical results was one of the major achievements of Herzberg's book. It is a matter of deep regret to us both that we cannot present our book to ‘GH’ for, hopefully, his approval. On the other hand, we were both privileged to spend time working in the laboratory in Ottawa directed by GH, and to have known him as a colleague, mentor and friend.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.423
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.4230.303

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 head0.010
GPT teacher head0.187
Teacher spread0.176 · 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 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

Citations67
Published2003
Admission routes1
Has abstractyes

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