File size: 2,165 Bytes
4b84361
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
# Capability Framework

This benchmark evaluates clinical reasoning quality across nine structured tasks.

The benchmark does not focus on diagnosis.

It focuses on whether a model can reason about stability, trajectory, boundary pressure, recovery, and intervention choice.

## Capability Domains

### State Reasoning

Dataset:

- clinical-compensation-vs-recovery-v0.2

Tests whether a model can distinguish visible stability from true recovery.

Core distinction:

- stable because recovered
- stable because supported

### Trajectory Reasoning

Datasets:

- clinical-silent-failure-v0.2
- clinical-trajectory-awareness-v0.2

Tests whether a model can distinguish current appearance from direction of movement.

Core distinctions:

- mild-looking but worsening
- severe-looking but improving
- hidden deterioration before collapse

### Decision Reasoning

Dataset:

- clinical-escalation-discipline-v0.2

Tests whether a model can decide when monitoring is no longer enough.

Core distinction:

- high visible severity but improving
- moderate visible severity but deteriorating

### Boundary Reasoning

Dataset:

- clinical-constraint-pressure-v0.2

Tests whether a model can detect pressure on the patient system.

Core distinction:

- support needs
- reserve capacity
- direction of pressure

### Margin Reasoning

Dataset:

- clinical-boundary-distance-v0.2

Tests whether a model can estimate proximity to collapse boundary.

Core distinction:

- safe margin
- narrowing margin
- critical boundary proximity

### Recovery Reasoning

Datasets:

- clinical-recovery-geometry-v0.2
- clinical-recovery-energy-v0.2

Tests whether a model can distinguish real recovery from superficial improvement and estimate recovery burden.

Core distinctions:

- improvement in one marker versus structural recovery
- low recovery effort versus high recovery effort

### Intervention Reasoning

Dataset:

- clinical-competing-interventions-v0.2

Tests whether a model can compare competing stabilisation pathways.

Core distinction:

- best action is not always the most aggressive action
- intervention quality depends on patient state, response profile, and downstream risk