Access to the gated repository, StanfordAIMI/CheXpert-v1.0-512

🤗Datasets
1

I kindly request access to the gated repository, StanfordAIMI/CheXpert-v1.0-512 on Hugging Face.

I intend to use the dataset for my ongoing research on artificial intelligence in medical imaging. I have made a request, and the status still remained pending.

Thanks

2

Access to gated datasets like StanfordAIMI/CheXpert-v1.0-512 is controlled directly by the dataset owners (Stanford AIMI), not by the Hugging Face community. If your request is still pending, it usually means the maintainers have not yet reviewed or approved it.

A few things you can do:

  • Make sure your Hugging Face profile is complete (name, affiliation, research purpose).
  • Add a short justification in the access request explaining your medical‑imaging research.
  • If the dataset has a linked license or external approval form, fill that out as well.
  • Sometimes approval takes several days depending on the maintainers’ schedule.

The community cannot grant access, but your request will be processed once the dataset owners review it.

3

Thank you @negdev.

I will continue to wait in anticipation for the approval.

4

Slot specification: each field declares which sources are allowed

SLOT_SPEC = {
“intent”: {“sources”: [“user_answer”]},
“target”: {“sources”: [“user_answer”, “pre_set_data”]},
“action”: {“sources”: [“user_answer”, “pre_set_data”]},
}

ALLOWED_ACTIONS = [“read”, “write”, “search”, “update”]

Storage for audit trail

RECORDS = {}

def verify(model_output, model_sources):
“”"
model_output: {“intent”: “…”, “target”: “…”, “action”: “…”}
model_sources: {“intent”: “user_answer”, “target”: “model_guess”, …}

This function:
- checks if each slot has a value from an allowed source
- marks slots as UNKNOWN if the source is invalid
- prevents model-invented values from being treated as valid
- returns a record instead of a boolean
"""

record = {
    "slots": {},
    "unknown_count": 0,
    "errors": []
}

for slot, spec in SLOT_SPEC.items():
    if slot not in model_output:
        record["slots"][slot] = {"value": None, "state": "UNKNOWN"}
        record["unknown_count"] += 1
        record["errors"].append(f"Missing slot: {slot}")
        continue

    value = model_output[slot]
    source = model_sources.get(slot, "model_guess")

    if source not in spec["sources"]:
        record["slots"][slot] = {"value": None, "state": "UNKNOWN"}
        record["unknown_count"] += 1
        record["errors"].append(
            f"Slot {slot} has invalid source '{source}'"
        )
    else:
        record["slots"][slot] = {"value": value, "state": "OK"}

# Action legality check
action_slot = record["slots"]["action"]
if action_slot["state"] == "OK":
    if action_slot["value"] not in ALLOWED_ACTIONS:
        record["errors"].append(f"Illegal action: {action_slot['value']}")

return record

def store(action_key, record):
RECORDS[action_key] = record

def execute(action_key):
“”"
Execution reads the stored record instead of calling verify().
This avoids the forbidden pattern: execute() branching on verify().
“”"
record = RECORDS.get(action_key)

if not record:
    return {"status": "blocked", "reason": "No verification record"}

if record["errors"] or record["unknown_count"] > 0:
    return {"status": "blocked", "reason": record["errors"]}

action = record["slots"]["action"]["value"]
return {"status": "executed", "result": f"Performed {action}"}

Example:

model_output = {“intent”: “fetch”, “target”: “file”, “action”: “delete”}

model_sources = {“intent”: “user_answer”, “target”: “model_guess”, “action”: “model_guess”}

record = verify(model_output, model_sources)

store(“run_001”, record)

print(execute(“run_001”))

Thanks for the detailed clarification — it helped me understand the two missing pieces in my initial implementation.

I’ve updated the code to follow the spec correctly:

• each slot now declares its allowed sources
• values from undeclared sources become UNKNOWN instead of being accepted
• verify() produces a full record (slot states, sources, unknown_count, errors)
• the record is stored and execute() reads it, avoiding the forbidden verify→branch pattern
• blocked runs are now fully recorded, so near‑misses don’t disappear

The example you pointed out (“intent: fetch” + “action: delete”) now behaves correctly: both fields are present, but the action comes from a model‑invented source, so the slot becomes UNKNOWN and execution is blocked with a proper record.

This aligns with §3.5: execution depends on the stored verdict, not on a fresh validation call. Thanks again for the guidance — the spec makes a lot more sense when implemented this way.