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Record W3179399555

Stem Cell Award

2021· article· en· W3179399555 on OpenAlexaboutno aff
Suzanan Tay

Bibliographic record

VenueJournal of Cancer Science and Research · 2021
Typearticle
Languageen
FieldMedicine
TopicBiomedical Ethics and Regulation
Canadian institutionsnot available
Fundersnot available
KeywordsStem cellStem cell biologyEngineering ethicsPolitical scienceLibrary scienceEngineeringBiologyComputer science
DOInot available

Abstract

fetched live from OpenAlex

Meetings International is announcing Young Scientist Awards through International Conference on Stem Cell (Stem Cell 2021) which is scheduled at Toronto, Canada during November 17-18, 2021. This Stem Cell focuses on “Exploring the new trends & horizons of stem cell research Stem Cell 2021and upcoming Conference will recognize participants who have significantly added value to the scientific community of Stem Cell and provide them outstanding Young Scientist Awards. The Young Scientist Award will provide a strong professional development opportunity for young researches by meeting experts to exchange and share their experiences at our international Conference

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)0.006
metaresearch head score (Gemma)0.008
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: Other
Teacher disagreement score0.202
Threshold uncertainty score0.676

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0030.001
Scholarly communication0.0070.002
Open science0.0020.005
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.2020.098

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 head0.120
GPT teacher head0.488
Teacher spread0.368 · 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
Published2021
Admission routes1
Has abstractyes

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