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Record W2806689491 · doi:10.15173/ijrr.v1i1.3327

Benefits and limitations of implementing videoconferencing for forensic psychiatry assessment in France

2018· article· en· W2806689491 on OpenAlexaff
Sébastien Prat, Robert Courtois

Bibliographic record

VenueInternational Journal of Risk and Recovery · 2018
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsMcMaster UniversitySt. Joseph’s Healthcare Hamilton
Fundersnot available
KeywordsVideoconferencingForensic psychiatryTelemedicineForensic scienceField (mathematics)Order (exchange)PsychiatryPsychologyComputer scienceMedicinePolitical scienceTelecommunicationsLawBusiness

Abstract

fetched live from OpenAlex

Telemedicine has been successfully used for many years in North America for the purpose of conducting forensic assessments. France, however, has not yet implemented this potentially useful tool. French forensic psychiatry could get inspired by this success in order to improve the practice of court ordered psychiatric assessments. In this article, we address the benefits and limitations of videoconferencing in the field of forensic psychiatry. Using these new means of telecommunications could help solve some of the issues encountered in France. (article in French)

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.519
Threshold uncertainty score0.182

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 head0.038
GPT teacher head0.363
Teacher spread0.325 · 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
Published2018
Admission routes1
Has abstractyes

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