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Record W4366549629 · doi:10.26434/chemrxiv-2023-h05hr

INSPIRE: Development of an Interdisciplinary Summer Program in Research and Entrepreneurship

2023· preprint· en· W4366549629 on OpenAlexafffund
Abootaleb Sedighi, Tudor B. Radu, Qirat F. Ashraf, Balmiki Kumar, Erica J. Quilates, Rima Rahmatullah, Joshua N. Milstein

Bibliographic record

VenueChemRxiv · 2023
Typepreprint
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsUniversity of Toronto
FundersUniversity of Toronto
KeywordsEntrepreneurshipEngineering ethicsPrincipal (computer security)Work (physics)Graduate studentsFace (sociological concept)Undergraduate researchEngineeringEngineering physicsMathematics educationChemistryMedical educationSociologyPsychologyPolitical scienceComputer scienceMedicineMechanical engineeringSocial science

Abstract

fetched live from OpenAlex

We developed the Interdisciplinary Science Program in Research and Entrepreneurship (INSPIRE) to address the changing career landscape that students with an interest in Physical Chemistry, Biophysics and Biochemistry face. Third and fourth-year undergraduate Chemistry and Physics students participated in a 4-week, hands-on program that introduced applications of biophysical and biochemical techniques to drug discovery, while simultaneously engaging in a crash course on entrepreneurship and pharma. The principal objective of the program was to introduce students to the interdisciplinary nature of Chemistry and Physics research in the Life Sciences while simultaneously introducing the idea of translating their future graduate work into a career in biotechnology.

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)0.008
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0020.008
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0180.008

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 head0.151
GPT teacher head0.396
Teacher spread0.245 · 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
GenreOther

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 routes2
Has abstractyes

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