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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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score0.788

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.041
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2018
Admission routes1
Has abstractyes

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