Session Kit: Module 05: Electron Microscopy and Image Basics
Everything needed to run Module 05 as a taught session: prep, timing, materials, misconceptions, rubric.
Generated from modules/module05.md. Edit the module page, not this file.
At a glance
| Duration | 4 hours |
| Capability target | Evaluate EM image patches for artifact risk and issue a justified pass/rework recommendation. |
| Learners leave with | Completed QA worksheet for all six patches |
Before you walk in
- You can state the capability target in one sentence without reading it.
- You have one worked example you will narrate, including where you are unsure.
- Data access works — accounts, viewer, notebook — verified today, not last week.
- The rubric is visible to learners before they start, not after.
- You have decided what “uncertain” earns, and you will say so out loud.
Learners should arrive having covered:
- Modules 01-04
Materials
Run of show
| Time | Segment | Your note |
|---|---|---|
| 00:00-08:00 | EM basics refresher | |
| 08:00-20:00 | Artifact recognition walkthrough | |
| 20:00-34:00 | Learner triage round | |
| 34:00-46:00 | QA threshold debate | |
| 46:00-56:00 | Decision logging practice | |
| 56:00-60:00 | Competency check |
The activity
Scenario: Your team has received pilot images from a new ssTEM acquisition of mouse visual cortex. The imaging facility reports that initial sections looked good, but they encountered intermittent knife chatter starting around section 200 and a possible staining gradient in the lateral third of the field of view. Before the facility commits to imaging the remaining 800 sections, your team must evaluate the pilot data and deliver a go/no-go recommendation with conditions.
- Survey (10 min): Open the six provided image patches (three from the clean region, three from the reported problem areas). For each patch, independently record: modality confirmation, visible artifacts, and an initial severity impression.
- Artifact classification (15 min): Using the artifact reference card, formally classify each artifact by type and assign a severity score (1 = minor, cosmetic; 2 = moderate, segmentation-affecting; 3 = severe, reconstruction-blocking). Map each artifact to its expected segmentation consequence (merge, split, or topology break).
- Spatial pattern analysis (10 min): Arrange the patches by their spatial position in the volume. Determine whether the artifacts are spatially correlated (e.g., staining gradient affecting one side consistently) or random. Spatially correlated artifacts require different mitigation than random ones.
- Cost-benefit analysis (10 min): For each artifact, estimate the downstream cost if the facility proceeds without fixing it. Consider: how many proofreading hours per affected section? How many sections are likely affected? Compare this to the cost of pausing acquisition for knife replacement or re-staining.
- Recommendation memo (15 min): Write a one-page memo to the imaging facility with your team’s recommendation. The memo must include: (a) a summary table of artifacts found, (b) your go/no-go decision with conditions, (c) specific remediation steps if you recommend pausing, and (d) a monitoring plan if you recommend proceeding.
What learners hand in
- Completed QA worksheet for all six patches
- Spatial artifact map (annotated sketch or diagram)
- One-page recommendation memo with summary table
Misconceptions to target
These are the errors this session exists to prevent. Surface them in the debrief rather than pre-empting them in the lecture — a misconception a learner has voiced is far easier to correct than one they are holding silently.
- They may believe: You can proofread your way out of a bad image.
- Surface it by asking: “What would have to be true for that to hold? What would change your mind?”
- They may believe: A noisy image is worse for segmentation than a clean image with faint membranes.
- Surface it by asking: “What would have to be true for that to hold? What would change your mind?”
- They may believe: Artifact severity can be judged from a count, when the spatial distribution matters more.
- Surface it by asking: “What would have to be true for that to hold? What would change your mind?”
- They may believe: Quality assessment is a clerical checkpoint rather than a scientific judgment that propagates through every downstream claim.
- Surface it by asking: “What would have to be true for that to hold? What would change your mind?”
Naming the norm
Every session is a chance to make one piece of the hidden curriculum explicit. Pick a moment where you would normally just do the professional thing, and say out loud why you are doing it — then ask whether anyone was taught that.
For this session, the candidate is whichever norm the activity most depends on: stating an assumption in the same sentence as the claim, recording the version a number came from, or saying “uncertain” and having it count as a real answer. See the hidden curriculum for the collected set and why naming them is a fairness intervention rather than etiquette.
Assessment
- Minimum (pass): Accurate identification of major artifacts across all patches, correct mapping to segmentation error type, and a defensible pass/flag/rework decision for each patch.
- Strong (merit): Clear articulation of cost tradeoffs, consistent severity thresholds across patches, spatially aware analysis, and a well-structured recommendation memo with specific conditions.
- Failure: Artifact labels assigned without reference to downstream segmentation implications, or QA decisions made without documented rationale.
Grade the reasoning, not the answer. A correct call with no evidence chain should not outscore a well-reasoned incorrect one — and saying so publicly changes behavior within one session.
Exit prompt
Pick one artifact and explain how it could create a merge or split error later. Then estimate: if this artifact appears on 5% of sections, how many additional proofreading hours would it add to a 1000-section volume?
If this session goes wrong
- Nobody talks in the debrief. You asked “any questions?” Ask instead: “Which cue would you drop first if the data got worse?”
- Everyone finishes early. They are pattern-matching, not judging. Give an ambiguous case where the answer is “uncertain” and see what happens.
- Nobody finishes. The scaffolding came off too fast. Work the next case together rather than pressing on.
- A learner is silently lost. The most likely cause is unstated vocabulary. Point them at the dictionary and check back.