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Evidence record 18346 · automatically gathered

This AI tool claims to pick the top 1% of preprints. Should researchers trust it?

QED Science says that its metrics reduce bias by assessing papers solely on the basis of their originality and validity.

Record details

Published: 9 August 2026
Source: Nature Machine Intelligence
Category: Research
Topics: Bias & fairness
Retrieved: 11 August 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Shared topic: Bias & fairness

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning

arXiv fairness query · 9 August 2026

Shared topic: Bias & fairness

F2STNet: Fair and Federated Spectral-Temporal Modeling for Graph Forecasting

arXiv fairness query · 10 August 2026

Shared topic: Bias & fairness

Let's Unlearn Stereotypes Before Decision-Making: Assessing the Impact of Intrinsic Bias Mitigation on Downstream Fairness in LLMs

arXiv cs.CY · 10 August 2026

Shared topic: Bias & fairness

Critical Acclaim Orientation in Large Language Models: Evidence from Film Preference Elicitation

arXiv cs.CY · 10 August 2026

Shared topic: Bias & fairness

Calibrating WEAT Against Anisotropy: ZCA Whitening as a Geometric Pre-Processing Step for Embedding Association Tests

arXiv cs.CY · 10 August 2026

Shared topic: Bias & fairness

FedTVD: Balancing Data Quality and Quantity for Robust Federated Learning

arXiv · 10 August 2026

How to cite this record

ethics.ai (9 August 2026), “This AI tool claims to pick the top 1% of preprints. Should researchers trust it?,” evidence record 18346, https://ethics.ai/record/18346 (originally published by Nature Machine Intelligence).

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