Correct stale claims in the user-facing docs

README omitted doubao from both places it lists supported video marks; the
mark has been registered since 2026-08-28 and docs/cli.md and
supported-signals.md already carry it. README also attributed the 2026-07-29
two-clip calibration to video-synthid-oracle.csv, which holds two rows from
one carrier dated 2026-07-31; that calibration was never recorded in a
tracked manifest, so say so rather than implying it is reproducible.

"Both surviving profiles" predates chroma-zimage; there are three. "The SDXL
profiles were removed" reads as false next to the shipped sdxl-zimage --
docs/synthid.md already had the right wording, naming the standalone SDXL and
ControlNet profiles, so use it in the other two places.

The Hub card declared a datasets entry for hugging-face/open-images, which
does not exist and rendered a dead link on the model page. Open Images stays
named in the prose, where it is a source rather than a Hub id.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

README.md

@@ -7,8 +7,8 @@ Remove AI provenance marks from images and video you generated yourself:
 - C2PA, EXIF, XMP, IPTC, and related AI metadata.
 
 Video support covers provenance identification, complete visible-plus-metadata
-cleaning, directory batches, visible Sora, Veo, Seedance, Dola, Hailuo AI, and
-Kling AI mark removal, and oracle-certified VAE regeneration for video SynthID
+cleaning, directory batches, visible Sora, Veo, Seedance, Doubao, Dola,
+Hailuo AI, and Kling AI mark removal, and oracle-certified VAE regeneration for video SynthID
 removal.
 
 > [raiw.cc](https://raiw.cc) runs this library as a hosted service, with the GPU
@@ -446,7 +446,7 @@ invisible removal.
   detail.
 - Visible video removal recognizes the moving Sora 2 wordmark, the current Veo
   diamond plus legacy `Veo` text, the Seedance boxed `AI` label, and the fixed
-  Dola, Hailuo AI, and Kling AI labels. It does not recognize the older Sora Turbo
+  Doubao, Dola, Hailuo AI, and Kling AI labels. It does not recognize the older Sora Turbo
   corner swirl or unregistered layouts from those providers.
   The classical OpenCV backend can smear structured backgrounds; use MI-GAN or
   LaMa when recovery quality matters.
@@ -486,8 +486,11 @@ reinterpret the pixel result returned `UNAVAILABLE`; that follow-up was not a
 verifier rerun and does not invalidate the built-in verdicts. A 2026-07-31
 full-clip check on a public eight-second Veo sample found `0.10` still detected
 and `0.15` not detected, so `0.15` is now the certified default. The
-reproducible hashes and verdicts live in
-`data/evaluations/video-synthid-oracle.csv`.
+reproducible hashes and verdicts for that full-clip check -- one carrier, two
+rows -- live in `data/evaluations/video-synthid-oracle.csv`. The earlier
+two-clip calibration is narrative only: its verdicts were not recorded in a
+tracked manifest, so treat the certified default as resting on the 2026-07-31
+rows.
 
 ## Documentation
 

docs/known-limitations.md

@@ -274,8 +274,9 @@ per-stage schedule, CFG 1.0 and CUDA.
 ### Small images are processed at their native size
 
 There is no minimum-resolution floor. It existed to enlarge small inputs toward
-SDXL's ~1024 training resolution and was removed with the SDXL profiles, which
-never applied it anyway. Both surviving profiles run at native geometry, so a
+SDXL's ~1024 training resolution and was removed with the standalone SDXL and
+ControlNet profiles, which never applied it anyway. The surviving `sdxl-zimage`
+is a different profile and is unaffected. All three surviving profiles run at native geometry, so a
 small input is neither enlarged before diffusion nor restored afterward.
 
 `--max-resolution` still caps very large inputs, and only ever scales down.

docs/photo-classify-hf/README.md

@@ -13,7 +13,6 @@ tags:
   - photo
   - provider-attribution
 datasets:
-  - hugging-face/open-images
   - detection-datasets/coco
 ---
 

docs/synthid.md

@@ -1092,7 +1092,7 @@ a resolution trend here; measure it.
 **Current implication:** the old floor table remains evidence about the dated
 test set, not the current resolver. The SDXL and ControlNet profiles it measured
 no longer exist; the shipped defaults are defined in `watermark_profiles.py`, and
-both surviving profiles run face repair as a built-in second stage rather than as
+all three surviving profiles run face repair as a built-in second stage rather than as
 an optional restore. Removal near a threshold remains seed dependent, so
 reproducible verification requires a fixed seed.