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RTT-MI-001
post-appendectomy day0
32M, low comorbidity
plateau_then_jump
Steps flat; Sleep improving
none
1) graded walking ladder 2) fixed sleep window 3) daily check-in
mobility; sleep; adherence
plateau_to_jump
effective_nudge
none
Under 160 words.
1 mobility nudge
RTT-MI-002
post-influenza day0
28F, athlete
decline_then_rebound
Early crash; HRV down
overexertion=1
1) exertion cap 2) hydration target 3) protein timing
load control; recovery fuel
crash_to_rebound
effective_nudge
none
Under 160 words.
1 crash control
RTT-MI-003
post-influenza day0
52M, work stress
oscillatory
Step spikes; sleep fragmented
stress=1
1) routine lock 2) evening wind-down 3) activity ceiling
variance reduction
oscillation_to_ascent
effective_nudge
none
Under 160 words.
1 variance lock
RTT-MI-004
post-knee-arthroscopy day0
61F, obesity
stalled_decline
Low steps; pain static
pain_risk=1
1) pain flare plan 2) chair-based physio 3) analgesic timing
pain control; mobility
stall_to_plateau
partially_effective
limited_mobility
Under 160 words.
1 pain-first
RTT-MI-005
post-appendectomy day0
44F, caregiver stress
stalled_decline
Sleep down; mood down
burnout=1
1) protected sleep block 2) daily social contact 3) task offload
sleep; social support
stall_to_plateau
effective_nudge
none
Under 160 words.
1 sleep-social
RTT-MI-006
post-influenza day0
30M, variable adherence
oscillatory
Spike-crash steps
adherence=0
1) step ceiling 2) reminder cues 3) recovery day rule
adherence; load
oscillation_to_ascent
effective_nudge
none
Under 160 words.
1 spike cap
RTT-MI-007
post-knee-arthroscopy day0
58M, obesity
stalled_decline
Steps declining
cardio_risk=1
1) aggressive exercise push 2) caloric restriction 3) bootcamp PT
overload
decline
risky
overload
Under 160 words.
1 avoid overload
RTT-MI-008
post-influenza day0
33F, anxiety
plateau_then_jump
Flat steps; worry language
anxiety=1
1) reassurance with metrics 2) exposure pacing 3) sleep anchor
fear reduction
plateau_to_jump
effective_nudge
none
Under 160 words.
1 fear reduction

What this dataset tests

Whether a model can recommend small, precise actions
that shift recovery into a more stable basin.

It ties actions to early signals.
It penalizes overload.

Typical failures

  • pushing intensity in stalled states
  • ignoring sleep or adherence signals
  • recommending generic advice without target

Suggested prompt wrapper

System

You propose micro-interventions to nudge recovery.

User

Predicted Topology
{predicted_topology}

Early Signals
{early_signals}

Risk Flags
{risk_flags}

Return

  • 3 micro-interventions
  • expected basin shift
  • one label

Citation

ClarusC64 dataset family

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