Evaluate log quality.

Evaluate log quality. is a detailed work activity in O*NET — a concrete unit of work shared across 3 occupations and seen in 5 occupation-specific tasks. It rolls up into the broader work activity Evaluate production inputs or outputs. in Judging the Qualities of Objects, Services, or People .

Detailed work activities are the most granular shared layer in O*NET's work-activity hierarchy (Generalized → Intermediate → Detailed → occupation-specific task). The figures below describe how this activity shows up across the economy and what independent studies measure about AI and this kind of work — not a prediction that the work will be automated.

AI exposure

Of the 5 tasks under this activity that the OpenAI / Eloundou “GPTs are GPTs” study rated, 3 (60%) are flagged as directly exposed to language models (E1) or exposed via model-powered tools (E2).

Exposure estimates overlap with model capabilities — whether a model could speed the task up — not whether the work will be done by software. Observed AI use is augmentation and assistance today, not jobs replaced.

Member tasks

Occupation-specific tasks O*NET maps to this detailed work activity, most important first.

• Evaluate log characteristics and determine grades, using established criteria. · Log Graders and Scalers · importance 4.7 · exposure with tools
• Assess logs after cutting to ensure that the quality and length are correct. · Fallers · importance 4.5 · exposure with tools
• Jab logs with metal ends of scale sticks, and inspect logs to ascertain characteristics or defects such as water damage, splits, knots, broken ends, rotten areas, twists, and curves. · Log Graders and Scalers · importance 4.3 · no direct exposure
• Identify logs of substandard or special grade so that they can be returned to shippers, regraded, recut, or transferred for other processing. · Log Graders and Scalers · importance 4.3 · exposure with tools
• Grade logs according to characteristics such as knot size and straightness, and according to established industry or company standards. · Logging Equipment Operators · importance 4.3 · no direct exposure

Occupations that perform this

• Log Graders and Scalers
• Fallers
• Logging Equipment Operators

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

• O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
• “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic

Data compiled June 2, 2026. Figures are estimates, not advice.

@misc{singulariki-evaluate-log-quality,
  title  = {Evaluate log quality.},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026},
  url    = {https://singulariki.com/detailed-activities/evaluate-log-quality}
}