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Record W2952265468 · doi:10.1002/ajmg.b.32735

Psychiatric genetic counseling: A mapping exercise

2019· review· en· W2952265468 on OpenAlexaff
Ramona Moldovan, Kevin A. McGhee, Domenico Coviello, Anniken Hamang, Angela Inglis, Charlotta Ingvoldstad Malmgren, Maria Soller, Mercy Laurino, Bettina Meiser, Lauren Murphy, Milena Paneque, Oleg Papsuev, Joanna Pawlak, Eulàlia Rovira‐Moreno, Clara Serra‐Juhé, Shiri Shkedi‐Rafid, Nakita Laing, Marie‐Antoinette Voelckel, Melanie Watson, Jehannine Austin

Bibliographic record

VenueAmerican Journal of Medical Genetics Part B Neuropsychiatric Genetics · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSpecialtyService (business)Genetic counselingProfessional developmentMedicineMedical educationPsychologyPsychiatryBusinessMarketing

Abstract

fetched live from OpenAlex

Psychiatric genetic counseling (PGC) is gradually developing globally, with countries in various stages of development. In some, PGC is established as a service or as part of research projects while in others, it is just emerging as a concept. In this article, we describe the current global landscape of this genetic counseling specialty and this field's professional development. Drawing on information provided by expert representatives from 16 countries, we highlight the following: (a) current understanding of PGC; (b) availability of services for patients; (c) availability of training; (d) healthcare system disparities and cultural differences impacting practice; and (e) anticipated challenges going forward.

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)0.002
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.004
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 head0.029
GPT teacher head0.330
Teacher spread0.302 · 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

Citations31
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Medical Genetics Part B Neuropsychiatric GeneticsSame topicBRCA gene mutations in cancerFrench-language works237,207