ArticleLaryngoscope investigative otolaryngology2026
Provenance, Not Prohibition: A Framework for AI in Scholarly Publishing.
Article in Laryngoscope investigative otolaryngology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Generative AI is now embedded in scholarly workflows, yet publishing policy has often jumped to permission or prohibition without first defining what is being governed. The central risk is not tool use itself, but loss of provenance: readers, reviewers, and editors must be able to trace how claims, citations, analyses, and interpretations were produced and verified. Harm is already measurable, including fabricated references, distorted summaries, hollow reviews, and disclosure policies that are widely ignored. This commentary proposes a practical framework centered on human accountability: separate capability from responsibility, prioritize provenance over polish, avoid unverifiable bans, and pair disclosure with explicit verification. Because AI now enters every stage of review, the unit of governance is not the static manuscript but the feedback loop around it, and the same obligations bind authors, reviewers, and editors alike. Journals should govern outcomes and professional standards rather than tool lists, building a culture of transparent use instead of surveillance.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.