diff --git a/scripts/r49-corpus/recover_eval_series.py b/scripts/r49-corpus/recover_eval_series.py
new file mode 100644
index 0000000..e7b120e
--- /dev/null
+++ b/scripts/r49-corpus/recover_eval_series.py
@@ -0,0 +1,38 @@
+"""Recover eval records a run's log emitted but its loss-series artefact dropped.
+
+Written because the seed-1 pilot's LossLog callback filtered on `"loss" in logs`,
+which excludes every eval record (Trainer emits `eval_loss` with no `loss` key).
+The data was never lost -- it was printed and not collected -- so it is parsed
+back out of the log rather than re-run. Idempotent: existing eval points are not
+duplicated.
+"""
+import ast, json, re, sys
+from pathlib import Path
+
+log, series = Path(sys.argv[1]), Path(sys.argv[2])
+s = json.loads(series.read_text())
+have = {p["step"] for p in s if "eval_loss" in p}
+found = []
+for m in re.finditer(r"\{[^{}]*'eval_loss'[^{}]*\}", log.read_text(errors="replace")):
+    try:
+        d = ast.literal_eval(m.group(0))
+    except Exception:
+        continue
+    d = {k: (float(v) if isinstance(v, str) and re.fullmatch(r"-?[\d.eE+]+", v) else v)
+         for k, v in d.items()}
+    found.append(d)
+# Trainer logs eval without a step field; epoch is present, so derive step order.
+added = 0
+for i, d in enumerate(found):
+    if d.get("epoch") is None:
+        continue
+    step = d.get("step")
+    if step is None:
+        after = [p["step"] for p in s if "loss" in p and p.get("epoch", 0) <= d["epoch"]]
+        step = max(after) if after else 0
+    if step in have:
+        continue
+    s.append({"step": step, **d}); have.add(step); added += 1
+s.sort(key=lambda p: (p["step"], "eval_loss" in p))
+series.write_text(json.dumps(s, indent=1))
+print(f"  recovered {added} eval records from {log.name} ({len(found)} found in log)")
diff --git a/scripts/r49-corpus/train_voice_lora.py b/scripts/r49-corpus/train_voice_lora.py
index 886d6d5..9e9e8b0 100644
--- a/scripts/r49-corpus/train_voice_lora.py
+++ b/scripts/r49-corpus/train_voice_lora.py
@@ -57,7 +57,12 @@ def pack(tok, records, seq_len):
 class LossLog(TrainerCallback):
     def __init__(self, path): self.path, self.series = path, []
     def on_log(self, args, state, control, logs=None, **kw):
-        if logs and "loss" in logs:
+        # ⚠ `"loss" in logs` DROPS every eval record, because Trainer emits eval
+        # under `eval_loss` with no `loss` key. The series then shows zero eval
+        # points, which reads as "no eval was run" rather than "the collector
+        # dropped it" -- an artefact silently omitting data that exists in the log
+        # a metre away. Accept any record carrying a loss of either kind.
+        if logs and ("loss" in logs or "eval_loss" in logs):
             self.series.append({"step": state.global_step, **{k: v for k, v in logs.items()
                                                               if isinstance(v, (int, float))}})
             Path(self.path).write_text(json.dumps(self.series, indent=1))