GPT-4o mini achieved the lowest ACT balance MAE (6.12) in replicating human supervisor ratings across 49 full transcripts¶
Claim · All claims
Evidence · 1 study · designr2·q2
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 i? Across 49 psychotherapy transcripts, GPT-4o mini achieved the lowest ACT balance MAE (6.12) among six evaluated LLMs, with statistically significant rank-order correlation with human ratings. → Pascal Riachi 2026
Evidence¶
Pascal Riachi 2026¶
Pascal Riachi, Sofie Kamber, Stella Brogna, Andrew Gloster, Rafael Wampfler. (2026). Toward Accessible Psychotherapy Training Using AI-Driven Interactive Patient Avatars. https://arxiv.org/abs/2606.17786 doi:10.48550/arxiv.2606.17786
q2 · i? · design · r2
Quantitative evaluation of six LLMs on 49 psychotherapy transcripts previously rated by a human ACT supervisor, comparing model-generated ACT-FM and TES ratings to human ratings via MAE and Spearman's ρ. GPT-4o mini's ACT balance MAE was 6.12 with ρ = 0.57; all models showed statistically significant rank-order correlation (p<.001).
"GPT-4o mini achieved the lowest ACT balance MAE (6.12), indicating closest absolute alignment with human supervisor ratings. All models showed statistically significant rank-order correlation with human ratings (p<.001)."
Discussion¶
Related Claims¶
- LLM choice significantly influences human-AI coding correspondence, with Claude Sonnet 4 performing best and GPT 4.1 Mini worst — related
- GPT-4o mini showed progressive turn-level convergence with accumulating context while larger models showed increasing or stable error — related
- LLM ratings of classroom transcripts are more correlated with each other than with expert human ratings, across the same and different tasks — related
- Models with similar rank correlations differ substantially in estimating difficulty magnitude (RMSE and MAE) — related
- Model and prompt choice account for only a small share of misalignment error, which concentrates in transcript-conditioned higher-order interactions — related
- Full-scale LLM versions consistently achieve higher agreement with human grades than their mini and nano counterparts — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
gpt-4o-mini-lowest-act-balance-mae |
title |
GPT-4o mini achieved the lowest ACT balance MAE (6.12) in replicating human supervisor ratings across 49 full transcripts |
description |
GPT-4o mini achieved the lowest ACT balance MAE (6.12) in replicating human supervisor ratings across 49 full transcripts |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2026 |
recheck_by |
2029 |
generated |
by process:wiki-ingest on 2026-10-10 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — pascal-riachi-2026 |
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