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Decision cockpit for pathology foundation-model benchmarking, built to move from broad coverage scans to task-level evidence.

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Task Evidence

SLN-Breast · sample_origin_type (SLN-Breast__target)

Tissue / Specimen Context / Tissue/Specimen Origin & Sampling Context

Inspect benchmark evidence for one task at a time: who leads, how stable the split-level results are, and which neighbouring tasks are likely to transfer intuition.

clsL1 · Tissue / Specimen ContextL2 · Tissue/Specimen Origin & Sampling Contextaxillary_lymph_nodesH&EAnchor evidence

Task metadata

Fields sourced from benchmark_main. Missing values are shown as —.

cls
Identity
task_key
SLN-Breast__target
dataset_name
SLN-Breast
task_name
sample_origin_type
task_type
cls
Taxonomy
task_family_l1
Tissue / Specimen Context
task_family_l2
Tissue/Specimen Origin & Sampling Context
label_structure
binary
num_classes
2
labels
{"0": "metastases", "1": "primary"}
Biology
organ
axillary_lymph_nodes
stain
H&E
specimen_type
lymph_node
timepoint
diagnosis
disease
乳腺癌（淋巴结转移）
Scale & Labels
patient_n
130
slide_n
130
label_source
pathology
label_visibility
direct
Result Evidence
result_tier
Anchor
result_quality_score
83.2
result_flags
—
result_tier_reason
Clear model separation: significant-win density 0.308.Difficulty sits in a usable range: best mean 0.958.
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