MétaCan
Menu
Back to cohort
Record W2941154199

How can we test if breast is best

2014· article· en· W2941154199 on OpenAlexaboutno aff
Clare Wilson, Catherine de Lange

Bibliographic record

VenueThe New Scientist · 2014
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsnot available
Fundersnot available
KeywordsBreastfeedingTest (biology)Work (physics)State (computer science)GerontologyPsychologyTerm (time)Breast feedingMedicinePediatricsComputer scienceEngineering
DOInot available

Abstract

fetched live from OpenAlex

Some of the common claims about the long-term benefits of breastfeeding--that it can boost IQ and protect against health conditions in later life--have been cast into doubt by a new study. Unsurprisingly, considering how contentious the issue of whether women should breastfeed is, the work has already been criticized. Cynthia Colen and David Ramey of Ohio State University in Columbus found no effect on IQ, but Michael Kramer at McGill University in Montreal Canada, questions their use of siblings because the decision to breastfeed one child and not the other isn't random.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.818
Threshold uncertainty score0.567

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)0.0000.000

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 head0.021
GPT teacher head0.278
Teacher spread0.257 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueThe New ScientistSame topicBirth, Development, and HealthFrench-language works237,207