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Record W4283774802 · doi:10.2196/34979

Representing Physician Suicide Claims as Nanopublications: Proof-of-Concept Study Creating Claim Networks

2022· article· en· W4283774802 on OpenAlex
Tiffany I. Leung, Tobias Kuhn, Michel Dumontier

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJMIRx Med · 2022
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsnot available
Fundersnot available
KeywordsCitationMisinformationSet (abstract data type)MedicinePublishingPsychologyFamily medicineComputer scienceWorld Wide WebComputer securityPolitical scienceLaw

Abstract

fetched live from OpenAlex

Background In the poorly studied field of physician suicide, various factors can contribute to misinformation or information distortion, which in turn can influence evidence-based policies and prevention of suicide in this unique population. Objective The aim of this paper is to use nanopublications as a scientific publishing approach to establish a citation network of claims in peer-reviewed publications about the rate of suicide among US physicians. Methods A list of articles from a previously published scoping literature review on physician suicide was used to identify those articles that commented on or investigated suicidal behaviors of physician populations, including students, postgraduate trainees, and practicing physicians. The included articles were from peer-reviewed publications and asserted a claim about the annual rate of physician suicide. Manual data extraction was performed to collect article (or resource) type, title, authors, digital object identifier or URI, publication year, claim (about annual physician suicide rate), data of last access of the article (eg, for a webpage), and citations supporting the claim. Additional articles, websites, or other links were only added to the set of claims if they were cited by a peer-reviewed article already included in the data set. A nanopublication was created for each article or resource using Nanobench with an investigator-developed literature-based claim nanopublication template. Results A set of 49 claims concerning the rate of US physician suicide was represented as nanopublications. Analysis of the claim network revealed that (1) the network is not fully connected, (2) no single primary source of the claim could be identified, and (3) all end-point citations had a claim with no further citation, had no apparent claim, or could not be accessed to verify the claim. The nanopublication strategy also enabled the capture of variant claims published on a website. Conclusions Nanopublications remain to be adopted in broader scientific publishing in medicine, especially in publishing about physician mental health and suicide. This proof-of-concept study highlights an opportunity for more coordinated research efforts in the subject of physician suicide. Our work integrates these various claims and enables the verification of nonauthoritative assertions, thereby better equipping researchers to advance evidence-based knowledge and to make informed statements in the advocacy of physician suicide prevention. Representing physician suicide rate claims as nanopublications can be extended and improved in future work.

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)0.068
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.320
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0680.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.004
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0030.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.000

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 head0.578
GPT teacher head0.526
Teacher spread0.052 · 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