Phase 6: participation grading, gradebook passback, opt-out integrity

Ports the timing-neutral foregone-participation grading scheme from
participation_grades.R: answer quality (per-course level points) minus
a deduction for participation foregone through unavailability,
estimated by Monte Carlo simulation of the actual weighted draw and
averaged over when absences fall, plus a small form-filing incentive
for drawn-while-absent-without-opt-out days. Reason-blind and
luck-protected; zero-answer students floor to 0. Parameters
(allowance in SD units, passing line, form penalty, simulation
size/seed) are course settings. Verified against the R engine's
rendered 2026q2 reports via the new import-legacy command: quality and
availability match exactly, finals within Monte Carlo noise; dropped
students import as inactive enrollments and are excluded identically.

Grades are computed on demand into stored GradeRun snapshots and
reviewed on a grades page with CSV export and per-student reports
(also served to students via a publish toggle). Display scales map
points to UW 4.0, a threshold table (one-click import of the Canvas
course grading scheme), or raw points. Gradebook passback via AGS
sits behind a settings toggle with a review-then-push flow.

Opt-out withdrawals are now soft-deletes with a withdrawn_at audit
trail, and close when class begins (class days gained optional start
times), so availability records cannot be rewritten after the fact.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

README.md

@@ -103,6 +103,7 @@ configuration: add a custom parameter
 pronouns=$com.instructure.Person.pronouns
 course_start=$Canvas.course.startAt
 course_end=$Canvas.course.endAt
+grading_scheme=$com.instructure.Course.gradingScheme
 ```
 
 The course dates bound the schedule and date pickers; the tool works
@@ -115,6 +116,52 @@ fields). Pronouns appear on the live call card, printed call lists,
 and each student's own page. If the account has pronouns disabled,
 everything simply shows without them.
 
+## Opt-outs
+
+Students remove themselves from a day's cold-call list by picking the
+date on their page; nothing else is asked. There is deliberately no
+enforced submission deadline: an instructor running live calls in
+class gets up-to-the-second opt-outs automatically, while one who
+prints a call list beforehand should just tell students how much lead
+time they need (for example, "an hour or two before class"), since
+opt-outs after printing won't be on the paper.
+
+Withdrawing an opt-out is bounded, because un-opting-out after the
+fact would rewrite a student's availability record (and with it their
+participation grade): withdrawal closes when class begins, using the
+start time recorded on the schedule page, or at the start of the class
+day when no time is recorded. Withdrawals are also recorded rather
+than deleted — the opt-out export includes a withdrawn_at column, so
+the full history of changes survives.
+
+## Grading
+
+Final participation grades use the timing-neutral foregone-
+participation scheme (a port of the earlier participation_grades.R):
+a student's grade is the quality of their answers minus a deduction
+for participation they missed by being unavailable, estimated by
+Monte Carlo simulation of the actual weighted draw and averaged over
+when the absences fall, plus a small incentive penalty for being
+drawn while absent with no opt-out filed. The reason for an absence
+never matters, and luck of the draw never moves a grade. Parameters
+(allowance, passing line, penalties, simulation size) are per-course
+settings; grades are computed on demand, reviewed on the instructor's
+grades page, and shown to students only when the instructor publishes
+reports. With gradebook passback enabled, a review-then-push page
+sends the reviewed scores to Canvas via the Assignment and Grade
+Services; nothing is ever sent without explicit confirmation.
+
+Grades are computed in points out of 100 and displayed through a
+per-course scale: the built-in linear UW 4.0 map, a threshold table
+(letter grades, importable in one click from the course's own Canvas
+grading scheme), or raw points.
+
+The port was verified against the R engine's rendered reports from a
+real course: answer quality and availability match exactly; the
+simulated penalty agrees within Monte Carlo noise. `flask --app
+coldcall_lti import-legacy <dir>` imports a manual-era class directory
+for this kind of testing.
+
 ## Developing without Canvas
 
 Because a Developer Key takes institutional approval to get, the app