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Record W1846804699 · doi:10.1007/s12015-015-9627-3

In the Know and in the News: How Science and the Media Communicate About Stem Cells, Autism and Cerebral Palsy

2015· article· en· W1846804699 on OpenAlexafffund
Kimberly Sharpe, Nina Di Pietro, Judy Illes

Bibliographic record

VenueStem Cell Reviews and Reports · 2015
Typearticle
Languageen
FieldMedicine
TopicBiomedical Ethics and Regulation
Canadian institutionsVancouver Coastal HealthNeuroDevNetVancouver Coastal Health Research InstituteUniversity of British Columbia
FundersStem Cell Network
KeywordsCommitStem cellAutismAutism spectrum disorderCerebral palsyGeneral partnershipPsychologyInternet privacyMedicinePsychiatryPolitical scienceComputer scienceBiology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.017
metaresearch head score (Gemma)0.050
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.985
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.050
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0050.026
Scholarly communication0.0150.016
Open science0.0010.006
Research integrity0.0130.012
Insufficient payload (model declined to judge)0.0070.001

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 head0.054
GPT teacher head0.297
Teacher spread0.243 · 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 designQualitative
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

Citations29
Published2015
Admission routes2
Has abstractno

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