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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 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)0.036
metaresearch head score (Gemma)0.151
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.040
Threshold uncertainty score0.188

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.151
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.002
Science and technology studies0.0040.017
Scholarly communication0.0090.022
Open science0.0030.004
Research integrity0.0080.013
Insufficient payload (model declined to judge)0.0400.018

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 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
GenreCommentary

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

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