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Record W2891877139 · doi:10.31031/sbb.2018.01.000512

The Next Nobel Prize Must Go to the Eminent Tom Spears

2018· article· en· W2891877139 on OpenAlexaboutno aff
Sam Yosemite

Bibliographic record

VenueSignificances of Bioengineering & Biosciences · 2018
Typearticle
Languageen
FieldMedicine
TopicScience, Research, and Medicine
Canadian institutionsnot available
Fundersnot available
KeywordsPrejudice (legal term)ChemistryNanotechnologyLawPolitical scienceMaterials science

Abstract

fetched live from OpenAlex

One of the most inspiring stories in modern applied science begins in the hopeless concrete barrios of a Toronto neighborhood called Lawrence Park - and ends in triumph. It is the story of how a young bioengineer overcame deprivation and prejudice to establish himself as a global leader in two fields not usually conjoined: bioengineering and chemistry. Spears, who today is a youthful 53, has established the modern understanding that the engineering of living systems - bioengineering -owes much to chemistry at its tiniest level, the actions of molecules, atoms and their components.

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)0.004
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.106
Threshold uncertainty score0.355

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0050.002
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.1060.065

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 head0.041
GPT teacher head0.314
Teacher spread0.274 · 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
GenreCommentary

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

Citations1
Published2018
Admission routes1
Has abstractyes

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