Per Andrey: bypass the QuadCLT image_data mechanics entirely and feed the GPU
directly - the permanent RT shape (more data becomes GPU-memory-resident;
QuadCLT stays for geometry/poses only).

- CuasMotion.readRawImageData(): raw /jp4/ reader extracted from
  perSensorFromRawJp4 (oracle getJp4Tiff, one thread/sensor, instrumentation);
  perSensorFromRawJp4 rewired, behavior unchanged.
- CuasConditioning.conditionSceneToGpu(): raw read -> condition() with the
  CURRENT calibration (curt_calib-updated lwir scales/offsets/scales2 +
  per-pixel FPN from the scene QuadCLT) -> bind scene (saveQuadClt,
  conditional) -> clear hasNewImageData -> setBayerImages(data,true) force-H2D.
  The bayer guard (ebef0b23 fix) keeps the upload alive through
  interCorrPair's own setBayerImages(false). TELL if the guard ever breaks:
  results become identical to the prepared-data path.
- CuasPoseRT: curt_pose_raw flag (new checkbox 'Pose test raw-jp4 ingest (A2)')
  runs the ingest per scene before the fit; ingest failure coasts the
  prediction and records an empty CSV/hyper row (fail=-1).

Acceptance (recorded): A2 legitimately diverges from phase A (old
Photogrammetric Calibration was broken, frozen from unrelated footage) -
judge by A2's OWN dstored/corr-RMS/convergence; systematically worse = red flag.

mvn compile clean.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>