MétaCan
Menu
← Back to cohort
Record W4229715651 · doi:10.1093/pch/20.5.276

Book Review

2015· article· en· W4229715651 on OpenAlexaff
Kevin Coughlin

Bibliographic record

VenuePaediatrics & Child Health · 2015
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineComputer science

Abstract

fetched live from OpenAlex

Preemie Voices, the latest work by Dr Saroj Saigal, is a beautiful testimonial to the past, present and future of neonatology. It contains heartwarming and eye-opening stories penned by young adults who themselves experienced the challenges of being born at the extremes of prematurity. The unifying message of these stories is one of hope, encouragement and perseverance. The authors, many of whom have disabilities, tell an honest account of what life is like for neonatal intensive care unit (NICU) survivors facing the challenges associated with their preterm birth. In the words of Rebecca Smith, born at 26 weeks, “I won the battle and the war against prematurity, and if these mild deficits are the price to pay for being alive, then I can live with them.” Richard Blythin, born at 25 weeks, says, “[Preemies] have an amazing ability to surprise you, and they are far stronger than their seemingly fragile bodies may appear”. Allison Gallant, born at 27 weeks, sums it up by saying, “How do you say thank you for life?”. This book is a must read for parents who have experienced the challenges of preterm birth, graduates of the NICU and health care practitioners who care for them. These poignant, first-hand stories are complemented by chapters, written by Drs Saigal and Peter Rosenbaum, outlining the history of neonatology in Canada and abroad, and summarizing some of the seminal works that have emerged from a distinguished career in neonatal follow-up. Dr Saigal discusses the ethics, outcomes and quality-of-life indicators for extremely low birth weight survivors, and Dr Rosunbaum provides perspectives on disability in Canadian society – all firmly grounded in the voice of those who have experienced it first hand, as we are reminded by Ron Federchuk, 26 weeks, who says, “Perhaps a different term for disabilities would be different abilities, because that's really what we all have”. Preemie Voices helps us to understand prematurity and its outcomes from the perspective of those it impacts most – the NICU survivors and their families. Visit the website for more information: .

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)0.001
metaresearch head score (Gemma)0.006
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: Review · Consensus signal: Review
Teacher disagreement score0.286
Threshold uncertainty score0.956

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.2860.205

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 head0.023
GPT teacher head0.303
Teacher spread0.280 · 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
GenreReview

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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venuePaediatrics & Child Health→Same topicInfant Development and Preterm Care→French-language works237,207→