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Record W4362670587 · doi:10.54097/hset.v39i.6604

Social Media Platform Website for Autism People

2023· article· en· W4362670587 on OpenAlex
Haoming Zhang

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHighlights in Science Engineering and Technology · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Methods and Impacts
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsAutismPsychologySocial mediaApplied psychologyPsychiatryComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Mental diseases are serious problems nowadays, autism is one of the most common mental diseases. As we are living in a fast paced society, people are busy with working and provide support to their families and friends, mental diseases are easy to be neglected. The objective of this article is to explain how to develop a good social media platform for the people with autism. This article includes the methods of observation, interview, and questionnaire. The first step is to observe and interview a real person who is diagnosed to moderate autism. Next, this work will find out 50 potential autistic people by questionnaire 1, then there are 5 questions in questionnaire 2, and will be given to potential people with autism to answer. After that, the article will discuss the results, and giving possible solutions. This article will provide help for people who are interested in developing an online social platform for people with autism.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.699
Threshold uncertainty score0.383

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.037
GPT teacher head0.347
Teacher spread0.310 · 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