「millimeter resolution and you can move X-axle manual by hand control.」
segment 2 · 29.72s
Open questions · Human–AI collaboration
The AI formulates questions from the gap between what the source supports and what a learner still needs. An expert answer becomes a provenance-bearing graph node and updates the related process context.
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01 · QUESTION FORMULATION
The system does not plausibly fill gaps. It fixes the source-supported boundary, then asks only for learning-critical fields that remain unstated.
Ground speech, on-screen text, entities, and motion in time
Separate process, action, attention, and criteria
Find absent criteria, values, exceptions, rationale, or identity
Avoid leading the answer and retain source links
Add accepted evidence and mark the question resolved
02 · OPEN QUESTIONS
Select a question to inspect why it was generated, its evidence, and the exact graph patch an answer will create.
The source shows what to do but omits a governing force, amount, time, ratio, speed, or tolerance.
Stated purpose and workholding — The narration introduces the machine for reducing shim and plate thickness and states that it has a 100-watt powered magnetic table.
Controlled value or tolerance
v6-speech-table-axes03 · GRAPH UPDATE
Applying an answer immediately changes the question state and adds a human-verified evidence node.
04 · SOURCE CHECKS
Transcript, OCR, and neutral-ID checks are a separate provenance gate—not answers to the skill questions. They remain available below.
Listen and confirm whether the displayed source-language text matches the recording.
「millimeter resolution and you can move X-axle manual by hand control.」
segment 2 · 29.72s
「protection cover.」
segment 4 · 45.14s
「We can get good results with variable auxiliary plates.」
segment 6 · 72.62s
Continue with this source
Switching views preserves the same source hash across instruction, analysis, skill structure, evidence, and human review.