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Record W3202812249 · doi:10.18433/jpps32384

Abstracts of poster presentations at the 2021 virtual annual of the Canadian Society for Pharmaceutical Sciences.

2021· article· en· W3202812249 on OpenAlexvenueaboutno aff
Kristine Warman

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2021
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBiosimilars and Bioanalytical Methods
Canadian institutionsnot available
Fundersnot available
KeywordsNobel laureateLibrary sciencePharmaceutical sciencesPolitical scienceMedicineArtPharmacologyComputer science

Abstract

fetched live from OpenAlex

In 2021, the Canadian Society for Pharmaceutical Sciences (CSPS) partnered with the Pharmaceutical Society of Japan (PSJ) and the Canadian Chapter of Controlled Release Society (CC-CRS) to present its annual meeting in the virtual style. Keynote speakers included Professor Michael Houghton – 2020 Nobel Laureate, Director of Li Ka Shing Applied Virology Institute (LKSAVI), Professor, Department of Medical Microbiology & Immunology, University of Alberta, and Professor Yoshiharu Matsuura, Director, Center for Infectious Diseases Education and Research (CIDER), Osaka University, Japan.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.480
Threshold uncertainty score0.742

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.000
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.4800.174

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 head0.102
GPT teacher head0.434
Teacher spread0.332 · 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.

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

Citations1
Published2021
Admission routes2
Has abstractyes

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