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Record W2113765902 · doi:10.2196/resprot.2675

Portal for Families Overcoming Neurodevelopmental Disorders (PFOND): Implementation of a Software Framework for Facilitated Community Website Creation by Nontechnical Volunteers

2013· article· en· W2113765902 on OpenAlexafffundvenue
Xin Cynthia Ye, Isaiah Ng, Puya Seid-Karbasi, Tuhina Imam, Cheryl E Lee, Shirley Yu Chen, Adam Herman, Balraj Sharma, Gurinder Johal, Bobby Gu, Wyeth W. Wasserman

Bibliographic record

VenueJMIR Research Protocols · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsChild and Family Research InstituteUniversity of British Columbia
FundersBC Children's HospitalChildren's Hospital FoundationAlexander and Margaret Stewart Trust
KeywordsThe InternetDisseminationInformation DisseminationInternet privacyQuality (philosophy)World Wide WebPsychologyMedicineComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: The Portal for Families Overcoming Neurodevelopmental Disorders (PFOND) provides a structured Internet interface for the sharing of information with individuals struggling with the consequences of rare developmental disorders. Large disease-impacted communities can support fundraising organizations that disseminate Web-based information through elegant websites run by professional staff. Such quality resources for families challenged by rare disorders are infrequently produced and, when available, are often dependent upon the continued efforts of a single individual. OBJECTIVE: The project endeavors to create an intuitive Web-based software system that allows a volunteer with limited technical computer skills to produce a useful rare disease website in a short time period. Such a system should provide access to emerging news and research findings, facilitate community participation, present summary information about the disorder, and allow for transient management by volunteers who are likely to change periodically. METHODS: The prototype portal was implemented using the WordPress software system with both existing and customized supplementary plug-in software modules. Gamification scoring features were implemented in a module, allowing editors to measure progress. The system was installed on a Linux-based computer server, accessible across the Internet through standard Web browsers. RESULTS: A prototype PFOND system was implemented and tested. The prototype system features a structured organization with distinct partitions for background information, recent publications, and community discussions. The software design allows volunteer editors to create a themed website, implement a limited set of topic pages, and connect the software to dynamic RSS feeds providing information about recent news or advances. The prototype was assessed by a fraction of the disease sites developed (8 out of 27), including Aarskog-Scott syndrome, Aniridia, Adams-Oliver syndrome, Cat Eye syndrome, Kabuki syndrome, Leigh syndrome, Peters anomaly, and Rothmund-Thomson syndrome. The editor progress score was used to measure performance for a portion of sites. CONCLUSIONS: The PFOND system provides a convenient and structured Internet resource for the facilitated creation of information resources for families confronted by rare disorders. The system empowers volunteers to participate in the creation of quality content, while allowing for the inevitable turnover of contributors over time. The next phase of PFOND development will focus on volunteer participation in system development and community engagement.

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)0.008
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: Not applicable · Consensus signal: none
GenreCandidate signal: Software · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0030.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0190.007

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 head0.062
GPT teacher head0.468
Teacher spread0.407 · 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
GenreSoftware

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".

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Citations4
Published2013
Admission routes3
Has abstractyes

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