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Record W4360999907 · doi:10.1021/cen-10110-awards1

HIST award to Geoffrey and Marelene Rayner-Canham

2023· article· en· W4360999907 on OpenAlexaboutno aff
special to C EN Vera V. Mainz

Bibliographic record

VenueC&EN Global Enterprise · 2023
Typearticle
Languageen
FieldChemistry
TopicHistory and advancements in chemistry
Canadian institutionsnot available
Fundersnot available
KeywordsArt

Abstract

fetched live from OpenAlex

The winners of the 2023 Joseph B. Lambert HIST Award for Outstanding Achievement in the History of Chemistry are Geoffrey W. Rayner-Canham and Marelene F. Rayner-Canham . This award honors their work on the history of women in science, particularly British women chemists. Geoffrey Rayner-Canham is a professor emeritus at the Grenfall Campus, Memorial University of Newfoundland, and Marelene F. Rayner-Canham is a retired physics instructor from the same university. The Rayner-Canhams have written four books about forgotten historical women scientists: Harriet Brooks: Pioneer Nuclear Scientist ; A Devotion to Their Science: Pioneer Women of Radioactivity ; Women in Chemistry: Their Changing Roles from Alchemical Times to the Mid-Twentieth Century ; and Chemistry Was Their Life: Pioneering British Women Chemists, 1880–1949 . The pair was also major contributors to the book Women in Their Element: Selected Women’s Contributions to the Periodic System and have published a large number of papers

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 categoriesMeta-epidemiology (narrow)
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 score0.551
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.007
GPT teacher head0.261
Teacher spread0.254 · 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.

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
Published2023
Admission routes1
Has abstractyes

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