MétaCan
Menu
Back to cohort
Record W3102158486

Exploring medical and educational systems and their impacts on mental health diagnosis and treatment

2020· article· en· W3102158486 on OpenAlexaboutno aff
Lloyd C. Taylor

Bibliographic record

VenueJournal of psychiatry · 2020
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsnot available
Fundersnot available
KeywordsPresentation (obstetrics)Mental healthAnxietyPsychologyMedical educationWork (physics)Depression (economics)Argument (complex analysis)Health careMedicinePsychiatryPolitical scienceEngineering
DOInot available

Abstract

fetched live from OpenAlex

Recent work focusing on the importance of neuroscience as it relates to educational principles has brought into light significant organizational and systems-based problems that impact the application of these prinicples among high school and college age students. These challenges, coupled with the ever increasing time demands and financial needs of health care providers in the United States has created an environment where schools are not adequately equipped to address mental health concerns and providers are limited in the time and resources available to treat in the office. Subsequently, ever increasing numbers of school aged children are being prescribed medications to treat symptoms that may be an artifact of the structure of the school day and the structure of the health care systems in the United States. This poster presentation seeks to present the argument of the need to address the aforementioned concerns, especially in light of the ever increasing mental health difficulties facing high school and college age children in the United States. It will also compare and contrast the systems in place in Canada and the United States to demonstrate strengths and weaknesses. Emphasis will be placed on diagnoses of ADHD, Anxiety, and Depression among high school and college aged students. This presentation will attempt to assimilite work from the Fulbright experience and subsequent related clinical experiences.

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)0.000
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 score0.210
Threshold uncertainty score0.274

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.126
GPT teacher head0.363
Teacher spread0.237 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of psychiatrySame topicAttention Deficit Hyperactivity DisorderFrench-language works237,207