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Record W2929908665 · doi:10.1098/rsbm.2018.0026

Boris Peter Stoicheff. 1 June 1924—15 April 2010

2018· article· en· W2929908665 on OpenAlexafffundabout
H. M. van Driel

Bibliographic record

VenueBiographical Memoirs of Fellows of the Royal Society · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum optics and atomic interactions
Canadian institutionsUniversity of Toronto
FundersNational Research Council Canada
KeywordsVacuum ultravioletLibrary sciencePersonalityGovernment (linguistics)BiographyExtreme ultravioletBrillouin scatteringRaman spectroscopyEngineering physicsPhysicsPolitical scienceComputer scienceOpticsLaserPsychologyLawPsychoanalysisPhilosophy

Abstract

fetched live from OpenAlex

Boris Stoicheff was a pioneer in the use of high-resolution Raman spectroscopy at the National Research Council of Canada to elucidate the structural properties of molecules. He was also one of the first scientists to apply lasers to spectroscopy, investigating spontaneous and stimulated Raman and Brillouin scattering in liquids and solids at the University of Toronto. He later extended the range of tunable coherent sources into the vacuum ultraviolet (VUV) and extreme ultraviolet (XUV) regions down to 80 nm, allowing investigations of electronic states and their lifetimes for rare gas dimers. He authored 190 research and review articles as well as a biography of his postdoctoral mentor and later his senior colleague, Gerhard Herzberg. He used his keen insight, warm personality and strong personal skills to serve the scientific community in numerous administrative roles, including terms as president of the Canadian Association of Physicists and the Optical Society of America. His 24 PhD graduates and more than 20 postdoctoral fellows and visitors, all of whom benefitted from his strong mentoring skills and high standards, have gone on to prominent positions in academia, government and industry.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.268
Threshold uncertainty score0.599

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.234
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 designNot applicable
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
Published2018
Admission routes3
Has abstractyes

Explore more

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