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id
int64
1
10
adherence
stringclasses
2 values
dose_change
stringclasses
4 values
ae_signal
stringclasses
3 values
efficacy_signal
stringclasses
4 values
narrative_move
stringclasses
2 values
label
int64
0
2
signal
stringclasses
10 values
1
stable
none
low
strong
aligned
0
Stable adherence with no dose change. Low AE. Strong efficacy. Narrative matches data.
2
stable
reduce
high
strong
aligned
1
Dose reduction driven by AE. Efficacy remains strong. Narrative honest about safety tradeoff.
3
stable
increase
low
plateau
aligned
1
Dose increase justified by plateau with low AE and stable adherence. Narrative acknowledges uncertainty.
4
unstable
none
low
weak
aligned
1
Weak efficacy plausibly driven by nonadherence. Narrative states adherence uncertainty before conclusions.
5
stable
hold
high
moderate
aligned
1
Dose hold for AE with partial benefit. Narrative consistent with protocol constraints.
6
unstable
increase
moderate
weak
spin
2
Dose increase used to mask nonadherence and weak efficacy. Narrative claims dose was main limiter.
7
stable
increase
high
weak
spin
2
Narrative reframes poor efficacy while escalating despite high AE burden.
8
unstable
reduce
high
weak
spin
2
Narrative blames disease while AE and adherence drive missed dosing and decline.
9
stable
reduce
moderate
weak
aligned
1
Reduction for tolerability with weak efficacy. Narrative acknowledges potential exposure loss.
10
stable
none
low
weak
spin
2
Narrative declares success despite weak efficacy with no operational explanation.

Clinical Quad Adherence Dose Changes Adverse Events Efficacy Narrative v0.2

What this dataset does

It tests whether a model can classify coherence versus collapse in a clinical decision loop.

The loop couples four operational nodes plus narrative behavior.

Quad nodes

  • adherence
  • dose changes
  • adverse events
  • efficacy signal

Narrative node

  • aligned means the story matches data and constraints
  • spin means the story tries to justify a decision that the data does not support

Labels

0 coherent
1 tradeoff
2 collapse

What changed in v0.2

  • Added explicit narrative_move field
  • Tightened label meaning
  • New scorer with validation, confusion, and error samples
  • Order independent prediction matching by id

Files

data/train.csv
data/test.csv
scorer.py

Run scoring

python scorer.py --preds_csv predictions.csv --gold_csv data/test.csv

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