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Record W4238329138 · doi:10.1021/cen-09447-notw3

Young blood may not cure aging ills

2016· article· en· W4238329138 on OpenAlex
Elizabeth Wilson

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueC&EN Global Enterprise · 2016
Typearticle
Languageen
FieldMedicine
TopicDietary Effects on Health
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIntensive care medicine

Abstract

fetched live from OpenAlex

A new blood transfusion method may help resolve confusion over past experiments on the effects of giving young mouse blood to old mice and vice versa. In those experiments, the rodents’ circulatory systems were connected surgically. A team at the University of California, Berkeley, including bioengineer Irina M. Conboy and her husband, researcher Michael J. Conboy, used computer-controlled microfluidic pumps to exchange blood between young and old mice, so that each received 50% of the other’s blood (Nat. Comm. 2016, DOI: 10.1038/ncomms13363). After the transfusion, the mice were disconnected. Past studies that surgically connected old-young mice pairs have produced sometimes controversial evidence that seemed to point to young blood’s power to reverse age-related ills such as impaired cognition and cardiac function. The new work is “very interesting” and “raises significant questions about the original experiments,” says Michael Rudnicki, director of the regenerative medicine program at the University of Ottawa. The

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.008
GPT teacher head0.296
Teacher spread0.288 · 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