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Record W4402159349 · doi:10.1024/2674-0052/a000086

Conference report of the annual meeting of the International Society for Sports Psychiatry (ISSP), online, June 8, 2024

2024· article· en· W4402159349 on OpenAlexaffabout
Carla Edwards, Malte Christian Claussen

Bibliographic record

VenueSports Psychiatry · 2024
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsMcMaster University
Fundersnot available
KeywordsLibrary sciencePolitical sciencePsychologyPsychiatryComputer science

Abstract

fetched live from OpenAlex

The International Society for Sports Psychiatry (ISSP) held its annual meeting online for the 5 th consecutive year.While the COVID-19 pandemic initially necessitated the online version of the ISSP annual meeting in May 2020, the transition created an opportunity for increased attendance by its international membership.Subsequent member surveys identified that a majority of responding members preferred that the annual meetings continue to be held online.The ISSP represents worldwide excellence in Sports Psychiatry.Founded in 1994, the ISSP has contributed to substantial advancements in the science and practice of sports psychiatry for athletes of every age, race, and ability.Leaders of the ISSP have developed and continue to refine world-class courses and curricula for mental health in sports, author seminal papers/books, provide mentorship for developing sports psychiatrists, lead global coalitions in sports psychiatry, and provide care for athletes at major games events.Following a welcome address by ISSP President Dr. Carla Edwards (Canada), meeting attendees were treated to a keynote address by internationally renowned Sports Medicine physician, researcher, and gold medal-winning Paralympian Dr. Cheri Blauwet.

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)0.030
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0300.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.005
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.225
GPT teacher head0.445
Teacher spread0.221 · 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.

Study designNot applicable
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

Citations1
Published2024
Admission routes2
Has abstractyes

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