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Record W3006721512 · doi:10.3389/fpsyt.2020.00112

Editorial: Back to the Future: On the Road Towards Precision Psychiatry

2020· editorial· en· W3006721512 on OpenAlexaff
Brisa S. Fernandes, Stefan Borgwardt, André F. Carvalho, Johann Steiner

Bibliographic record

VenueFrontiers in Psychiatry · 2020
Typeeditorial
Languageen
FieldPsychology
TopicMental Health Research Topics
Canadian institutionsCentre for Addiction and Mental HealthUniversity of Toronto
Fundersnot available
KeywordsPsychiatryFront (military)MedicinePsychologyEngineering

Abstract

fetched live from OpenAlex

On the Road Towards Precision PsychiatryPsychiatry, with the field of Precision Psychiatry, has been experiencing one of the most exciting moments of its history with a paradigmatic shift (1).A few years ago, it became clear that the understanding of psychiatry at the time, mostly descriptive and phenomenologically based, was wanting.This led to a crisis within the psychiatric community, and, some would say, a disbelief in the field; the simply phenomenologically driven paradigm of the time was no longer sufficient.According to philosophy of science, when a paradigm is threatened by crisis, the community itself, in this case, the psychiatric community, with its clinicians and scientists, is in disarray.For instance, there are moving quotations from Wolfgang Pauli, one a few months before Heisenberg's matrix algebra, which was a major conceptual change in quantum mechanics, and one just some months after.In the former, Pauli expresses the feeling that physics is going to ruin, and he wishes he were in another field; a few months later, the way ahead is clear.At the time, many had the same feeling, and at the height of the crisis, the community was falling apart as the current paradigm was under questioning (2).Crisis and paradigm change go hand in hand; however, crisis does not, in itself, lead to rejection of the existing paradigm.The decision to reject one paradigm is invariable parallel to the decision to accept another, and the logic leading to that decision involves the comparison of both paradigms with each other.In this sense, precision psychiatry, by embracing the heterogeneity of psychiatric disorders, and thus aiming at predicting diagnosis, prognosis, and response to treatment for an unique individual by employing the underlying pathophysiology, as opposed to diagnosing and treating psychiatric disorders merely informed by the somehow subjective clinical characteristics of a patient, constitutes a new paradigm in psychiatry (1).A new paradigm is always accompanied by exciting new research, and the psychiatric scientific community is becoming fully committed to embracing Precision Psychiatry by actively conducting very high-quality science in the field.By presenting findings from previously separate fields of psychiatry, neurophysiology, and computational modelling, with the Research Topic "Back to the Future: On the Road Towards Precision Psychiatry," we were able to contribute to the advancement and to promote this new field.Precision Medicine has been defined as 'an emerging approach for treatment and prevention that takes into account each person's variability in genes, environment, and lifestyle' (3).In this Research Topic, research regarding biomarkers and the biosignature of psychiatric disorders was advanced.

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)0.031
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.030
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.031
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0040.002
Science and technology studies0.0050.003
Scholarly communication0.0090.006
Open science0.0040.002
Research integrity0.0160.018
Insufficient payload (model declined to judge)0.0300.026

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 head0.018
GPT teacher head0.356
Teacher spread0.338 · 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
GenreEditorial

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

Citations10
Published2020
Admission routes1
Has abstractyes

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