Claims

Blind expert raters judged VeriForge passages as conveying stronger perceived authorial domain competence, with other quality dimensions showing uncorrected trends

Claim · All claims
Evidence · 1 study (2 entries) · causal r1–r2 · q2 · i3 large
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person · recheck by 2029: tool and model accuracy changes quickly

Subclaims

Reading the evidence codes

q is the design tier, i the impact, n the sample, and the kind with its r the rigour judged within that kind: what each code means.

This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.

q2 i3 Perceived authorial domain competence was rated higher for VeriForge (M=4.58 vs M=3.58; r=.818) and remained significant after FDR correction. → Ruqi Sun 2026 q2 i? Natural integration (M=4.92 vs M=4.25; q=.065) and specificity (M=4.17 vs M=3.54; q=.065) showed positive trends that did not survive correction; the uncorrected composite favored VeriForge in 10 of 12 pairs. → Ruqi Sun 2026 (2)

Evidence

Ruqi Sun 2026

Ruqi Sun, Jiaping Li, Wenhui Tao, Ximing Zheng, Yuefeng Tan, Jiahao Wei, and Yuxin Ma. (2026). VeriForge: Mitigating Latent Knowledge Gaps in Narrative Drafting via Mixed-Initiative Scaffolding. https://arxiv.org/abs/2608.09698 doi:10.48550/arxiv.2608.09698

q2 · i3 · causal · r2

Blind expert rating by two published authors of anonymized story snippets on 7-point scales across three verisimilitude-informed dimensions; printed effect size r=.818; single-rater absolute-agreement ICCs were moderate (ICC(A,1)=0.53–0.59).

"Only perceived authorial domain competence remained significant after correction ( 𝑀= 4.58vs. 𝑀= 3.58; 𝑊= 2.5, 𝑝=. 005,𝑞=. 015,𝑟=. 818)."

Ruqi Sun 2026 (2)

Ruqi Sun, Jiaping Li, Wenhui Tao, Ximing Zheng, Yuefeng Tan, Jiahao Wei, and Yuxin Ma. (2026). VeriForge: Mitigating Latent Knowledge Gaps in Narrative Drafting via Mixed-Initiative Scaffolding. https://arxiv.org/abs/2608.09698

q2 · i? · causal · r1

Composite expert rating from the same blind evaluation (printed r=.770); both raters independently assigned higher scores to VeriForge snippets in the same 10 pairs despite moderate scoring variance. Word count did not differ (p=.532).

"The composite score was higher for VeriForge (𝑀= 4.56vs. 𝑀= 3.79; 𝑝=. 005,𝑟=. 770), with 10 of 12 pairs favoring the system; this composite test was uncorrected."

Discussion

Page metadata
Field Value
type claim
id veriforge-expert-domain-grounding-ratings
title Blind expert raters judged VeriForge passages as conveying stronger perceived authorial domain competence, with other quality dimensions showing uncorrected trends
description Blind expert raters judged VeriForge passages as conveying stronger perceived authorial domain competence, with other quality dimensions showing uncorrected trends
status review
evidence_strength weak
newest_evidence 2026
recheck_by 2029
generated by process:wiki-ingest on 2026-10-11
trust unverified — no one has confirmed this page's content
sources 2 — ruqi-sun-2026, ruqi-sun-2026-2

Frontmatter is the page's machine-readable record — see the Schema & Guide.