MétaCan
Menu
Back to cohort

Burden and Social Cost of Fetal Alcohol Spectrum Disorders

2016· book-chapter· en· W2522167713 on OpenAlexaff
Svetlana Popova, Shannon Lange, Larry Burd, Jürgen Rehm

Bibliographic record

VenueOxford University Press eBooks · 2016
Typebook-chapter
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFetal alcoholFetal Alcohol Spectrum DisorderIntervention (counseling)Criminal justicePsychiatryEconomic costBroad spectrumPublic healthMedicineEnvironmental healthHealth careMental healthBusinessPublic economicsPsychologyNursingEconomic growthCriminologyEconomicsPregnancy

Abstract

fetched live from OpenAlex

Abstract Damage to the central nervous system is a unifying concept for nearly all of the diagnoses that fall under the Fetal Alcohol Spectrum Disorders (FASD) umbrella. Thus, FASD are an important public health and social problem worldwide that consumes a large amount of resources, both economic and societal by imparting a large burden on society through such sectors as the healthcare system, mental health and substance abuse treatment services, foster care, the criminal justice system, and the long-term care of individuals with intellectual and physical disabilities. Existing estimates of the economic impact of FASD demonstrate significant cost implications on the individual, the family and society. Many of the costs associated with FASD can be reduced with the implementation of effective social policies and intervention programs.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.001

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 head0.016
GPT teacher head0.215
Teacher spread0.199 · 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

Citations18
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueOxford University Press eBooksSame topicPrenatal Substance Exposure EffectsFrench-language works237,207