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Record W4304207296 · doi:10.1089/cell.2022.0105

The 2022 International Society for Stem Cell Research (ISSCR) Annual Meeting: Celebrating 20 Years of Achievements

2022· article· en· W4304207296 on OpenAlexaff
Janelle Drouin‐Ouellet, Dan Li, Yuancheng Ryan Lu, Camila Vázquez Echegaray

Bibliographic record

VenueCellular Reprogramming · 2022
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsLibrary scienceEngineering ethicsEvent (particle physics)Stem cellBiologyEngineeringComputer science

Abstract

fetched live from OpenAlex

Last June, the stem cell community came together to celebrate the 20th anniversary of the International Society for Stem Cell Research (ISSCR), one of the leading organizations in the field. The hybrid event mixed a varied program filled with plenary talks, concurrent track sessions, poster presentations, exhibit booths, and plenty of opportunities to enhance stem cell research through bonding between academia and industry. This report highlights the Plenary sessions, with the main topics discussed by each speaker. All the impressive research showcased during the meeting is genuine proof of the great advancements the field has witnessed during these last 20 years, and the more to come.

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)0.007
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: Other · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0070.002
Open science0.0010.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0320.021

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 head0.037
GPT teacher head0.310
Teacher spread0.273 · 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
Published2022
Admission routes1
Has abstractyes

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