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Record W2735115889 · doi:10.1007/s10897-017-0115-6

A Report on Ten Asia Pacific Countries on Current Status and Future Directions of the Genetic Counseling Profession: The Establishment of the Professional Society of Genetic Counselors in Asia

2017· article· en· W2735115889 on OpenAlexaff
Mercy Laurino, Kathleen A. Leppig, Peter James B. Abad, Breana Cham, Yoyo Wing Yiu Chu, Saahil Kejriwal, Juliana Mei‐Har Lee, Darci L Sternen, Jennifer K. Thompson, Matthew Burgess, Shu Chun Chien, Niby J. Elackatt, Jiin Ying Lim, Thanyachai Sura, Sultana MH Faradz, Carmencita D. Padilla, Eva Cutiongco de‐la Paz, Donny Nauphar, Khanh Ngoc Nguyen, Olya Zayts, Dũng Chí Vũ, Meow‐Keong Thong

Bibliographic record

VenueJournal of Genetic Counseling · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsBC Cancer Agency
FundersTaiwan Foundation for Rare DisordersĐại học HuếQueen Mary University of London
KeywordsGenetic counselingGlobeProfessional associationProfessional developmentMedical educationEast AsiaPolitical scienceMedicineFamily medicineEconomic growthPublic relationsChinaGeneticsBiology

Abstract

fetched live from OpenAlex

The Professional Society of Genetic Counselors in Asia (PSGCA) was recently established as a special interest group of the Asia Pacific Society of Human Genetics. Fostering partnerships across the globe, the PSGCA's vision is to be the lead organization that advances and mainstreams the genetic counseling profession in Asia and ensures individuals have access to genetic counseling services. Its mission is to promote quality genetic counseling services in the region by enhancing practice and curricular standards, research and continuing education. The PSGCA was formally launched during the Genetic Counseling Pre-Conference Workshop held at the 11th Asia-Pacific Conference on Human Genetics in Hanoi, Viet Nam, September 16, 2015. The pre-conference workshop provided an opportunity for medical geneticists and genetic counselors from across 10 Asia Pacific countries to learn about the varied genetic counseling practices and strategies for genetic counseling training. This paper provides an overview of the current status and challenges in these countries, and proposed course of unified actions for the future of the genetic counseling profession.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.139
Threshold uncertainty score0.579

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.292
Teacher spread0.282 · 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 teacher head, 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

Citations35
Published2017
Admission routes1
Has abstractyes

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