Gemini and Gemini Pro show the highest internal grading consistency across file upload volumes, with no clear monotonic lost-in-the-middle effect¶
Claim · All claims
Evidence · 1 study · causalr1·q3
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.
q3 i? Across file upload volumes of 1–8 files, Gemini and Gemini Pro had the highest Krippendorff's alpha (Gemini Pro up to 0.702), and no monotonic relationship between volume and consistency was found. → Brevik A 2026
Evidence¶
Brevik A 2026¶
Brevik A, Jerpseth H and Lafontan SR (2026). Large language models as grading assistants in public health education: a method-comparison study of essay-style exam assessment. Front. Educ. 11:1904452. https://doi.org/10.3389/feduc.2026.1904452
q3 · i? · causal · r1
Krippendorff's alpha across single- and multi-file upload conditions (3, 5, 7/8 files). "Gemini and Gemini Pro appeared to be the most consistent" (Gemini Pro alphas 0.691–0.702); non-Google models showed lower alpha with multiple files, though the study lacked power to quantify U-shaped attention bias.
"Considering the grading consistency across different file upload volumes (Table 3), Gemini and Gemini Pro appeared to be the most consistent. No clear evidence of a lost-in-the-middle problem or attention fatigue can be discerned from"
Discussion¶
Related Claims¶
- ChatGPT in thinking mode shows the strongest agreement with human examiners on essay-style exam grading (weighted kappa 0.718) — related
- LLM-based essay grading is not fully reproducible: repeated ChatGPT sessions on the same submissions show only moderate consistency (Krippendorff's alpha 0.625) — related
- Within-judge variance of the repeated LLM-judge rubric is negligible, but cross-model-family agreement remains untested — related
- gpt-4o graded student submissions most correctly in almost all assignments, but gemini-1.0-pro graded the boolean-algebra assignment most correctly — related
- LLM agreement with human examiners is limited in fast mode and improves in reasoning or thinking modes — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
gemini-highest-consistency-across-file-volumes |
title |
Gemini and Gemini Pro show the highest internal grading consistency across file upload volumes, with no clear monotonic lost-in-the-middle effect |
description |
Gemini and Gemini Pro show the highest internal grading consistency across file upload volumes, with no clear monotonic lost-in-the-middle effect |
status |
review |
evidence_strength |
moderate |
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 |
1 — brevik-a-2026 |
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