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Assessing Effective Care in Normal Labor: The Bologna Score

2001· article· en· W2100584614 on OpenAlexaff
Beverley Chalmers, Richard Porter

Bibliographic record

VenueBirth · 2001
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsCoalition for Research in Women's HealthSunnybrook Health Science Centre
Fundersnot available
KeywordsApgar scoreHealth careMaternity careMedicineNursingPsychologyDemographic economicsEconomicsEconomic growthPregnancyBirth weight

Abstract

fetched live from OpenAlex

The intention of the "Bologna score" is to quantify, both in an individual labor and in a wider population, the extent to which labors have been managed as if they are normal as opposed to complicated. In this way it may be possible to assess both attitudes and practices within a maternity service toward the effective care of normal labor. A scoring system for normal labor was proposed at the World Health Organization (Regional Office for Europe) Task Force Meeting on Monitoring and Evaluation of Perinatal Care, held in Bologna in January 2000. This paper describes conceptual development of the scale. Recommendations for future evaluation of the Bologna score's validity and potential include field testing globally, comparison with the Apgar score, and evaluation of the relative weight contributed by each of the five measures comprising the Bologna score.

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)0.003
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.012
GPT teacher head0.302
Teacher spread0.290 · 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 designObservational
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

Citations46
Published2001
Admission routes1
Has abstractyes

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