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Record W3008652974 · doi:10.2217/rme-2019-0149

Portrayal of Umbilical Cord Blood Research in the North American Popular Press: Promise or Hype?

2020· article· en· W3008652974 on OpenAlexafffundabout
Alessandro R Marcon, David Allan, M. Barber, Blake Murdoch, Timothy Caulfield

Bibliographic record

VenueRegenerative Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicBiomedical Ethics and Regulation
Canadian institutionsCanadian Blood ServicesOttawa HospitalUniversity of OttawaUniversity of Alberta
FundersCanadian Institutes of Health ResearchGenome AlbertaCanadian Blood ServicesAustralian Government
KeywordsUmbilical cordNarrativeMedicineNarrative reviewCord bloodTransplantationMass mediaAdvertisingIntensive care medicineSurgeryBusinessInternal medicineImmunologyLiteratureArt

Abstract

fetched live from OpenAlex

Aim: This study examined how umbilical cord blood (UCB) use was portrayed in the English language North American popular press. Methods: Directed content analysis was conducted on 400 articles from 2007 to 2017 containing ‘cord blood,’ published by the most read Canadian and American news sources. Results: A total of 86.3% of the articles detailed UCB treatments and therapies, the majority of which align with clinical evidence. Some articles portrayed speculative/experimental therapies as efficacious. Public and private banking initiatives received substantial attention, and were portrayed diversely. Promotional narrative messaging was evident around private banking. Conclusion: Findings demonstrate the need for continual monitoring of the media portrayals of UCB as stem cell and transplantation research develops and as clinics continue to operate.

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)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.997
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.006
Science and technology studies0.0030.006
Scholarly communication0.0100.005
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.269
GPT teacher head0.433
Teacher spread0.164 · 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

Citations6
Published2020
Admission routes3
Has abstractyes

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