C Evidence Grade C Use with Hedging Current

65.7%

65.7% — performance benchmark for N-MNIST (2026)

Name: Performance Benchmark Statistics
Creator: Lighthouse Research
Published: 2026-04-14

2026 · Unknown · Mitsubishi Heavy Industries

Cite this stat Share How we verify

Source: Mitsubishi Heavy Industries View source

Curated by Aaron Agius · Founder, Louder Online

Last verified: 2026-06-04 · How we verify data →

Source verified Evidence graded

Value

65.7%

Unit

Percentage

Data Vintage

2026

Entity

N-MNIST

Study Type

Unknown

Trend

Increasing

Evidence Quality

Moderate quality evidence

Useful directional data with some methodological gaps. Treat as indicative rather than definitive — corroborate before citing in formal research.

53/100 confidence

Score breakdown

Extraction

Source Trust

Citation Chain

Independence

Methodology

Freshness

Sources (24)

Mitsubishi Heavy Industries Primary Tier A

https://www.mhi.com/jp/business/products-services/industrial-machinery/industrial-heat-pumps/heat-pu… ↗

Confidence: 54/100 Vintage: 2026

Source Article

業務用給湯器（エコキュート）業務用給湯器（エコキュート）地球の空気がエネルギー。自然冷媒CO2ヒートポンプ給湯機は、空気の熱を利用して90℃の温水を作ります。三菱重工グループの冷熱事業を推進する三菱重工サーマルシステムズ株式会社が展開する業務用エコキュートQ-tonシリーズは、オゾン破壊係数がゼロの冷媒を採用しています。－25℃外気温まで90℃の温水供給が可能で、燃焼式給湯機（ボイラー）に比べて年間CO2排出量約65%、ランニングコスト約66%の削減という高効率を実現しています。この製品の取り扱い会社：

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Original Research

arXiv · Original study ↗

Methodology

Results from Sharpness-Aware Surrogate Training on N-MNIST benchmark.

Study: Unknown

Cite this stat

Suggested hedging: based on claims without stated methodology, with unverified sample sizes...

Plain Text

N-MNIST: 65.7% performance benchmark. Source: Mitsubishi Heavy Industries (2026). Via Lighthouse Research Data — https://lighthousedata.io/data/n-mnist-hard-spike-accuracy-improvement

HTML Embed

<blockquote cite="https://lighthousedata.io/data/n-mnist-hard-spike-accuracy-improvement" style="border-left:3px solid #2563eb;padding:12px 16px;margin:16px 0;font-family:system-ui,sans-serif;background:#f0f4ff;"><strong>65.7%</strong> — performance benchmark for N-MNIST<br><small>Source: Mitsubishi Heavy Industries (2026) · <a href="https://lighthousedata.io/data/n-mnist-hard-spike-accuracy-improvement" target="_blank" rel="noopener">Lighthouse Data</a></small></blockquote>

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