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Feroze Novroji Ghadially, 1920-2014: A Personal Remembrance

2015· article· en· W2419488815 on OpenAlexaboutno aff
Peter B. Marcus

Bibliographic record

VenueBaylor University Medical Center Proceedings · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMolecular Biology Techniques and Applications
Canadian institutionsnot available
FundersBaylor Scott and White Health
KeywordsGeniusBiographyTributeCharismaFriendshipWishArtArt historyHistoryClassicsLiteraturePsychologyPhilosophy

Abstract

fetched live from OpenAlex

On December 28, 2014, the last of my trio of heroes in the pathology world passed away (1). This one-of-a-kind eccentric genius, so beloved by all who knew him, stood astride the world of ultrastructural pathology during its heyday in the 20th century like a colossus. Feroze Ghadially (Figure 1) was also my friend, and it is to this remarkable man, one of the preeminent pathologists of the 20th century, that I wish to pay tribute to with this personal remembrance. Figure 1. Dr. Ghadially at his electron microscope at the University of Saskatchewan, Saskatoon, circa 1980 (age 60). Dr. Ghadially was acutely aware of his own outstanding abilities and accomplishments and—refreshingly—was not shy about mentioning them. On the other hand, he was able to chuckle at his own idiosyncracies and eccentricities. His disarming ability to laugh at himself is reflected in much of what I write here about his remarkable life and of our friendship of 40 years. This includes direct quotes of some of the funnier things he said during our many telephone chats; they are taken from notes made by me during these conversations. The enigma that was the brilliant, charismatic Dr. Feroze Ghadially is best understood by first taking a look at the history of his earlier life and career—the years before I first met him. These anecdotes (and some from later years) are from a tongue-in-cheek biography of himself that Dr. Ghadially wrote, in the third person, for a monograph celebrating a decade of Killam Program laureates (2). I have placed the extracts from this biography (actually autobiography) in quotation marks.

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 score0.250
Threshold uncertainty score0.646

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)0.0000.000

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 head0.013
GPT teacher head0.232
Teacher spread0.219 · 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
Published2015
Admission routes1
Has abstractyes

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