We present AnchorFlow-VIO, an open-source Basalt-derived monocular visual-inertial odometry system, and evaluate a uniform configuration on LaMAria. The system uses one grayscale camera and one IMU, combining factory IMU correction, a fixed timing adjustment, windowed initialization and fixed-template patch tracking. Server evaluation of all 63 test recordings yields control-point scores of 47.2, 37.1, 24.8, 35.1 and 15.6 for Short, Medium, Long, Low light and Moving platform. Test pose recalls at 5 m are 84.6%, 69.1%, 53.9% and 62.9% for the four categories reporting dense recall. On ten training recordings, mean control-point score is 41.38 and all 265,694 image timestamps receive poses, including 204 filled poses. One training platform recording diverges and scores zero. A paired four-record comparison favors fixed over rolling templates on three recordings, while reversing that ranking on the fourth. Increasing feature density also yields mixed results. Ten fresh runs at prospectively fixed 30 s and 120 s offsets expose substantial start sensitivity: a low-light recording scores 6.14 at the earlier start and 42.00 at the later start. These results characterize the limits of the frozen system and show why complete output, feature counts and selected successful runs are insufficient evidence of robust localization. Source code, frozen configuration and reproducible submission tools are publicly available; training ablations are reported separately from the submitted test evaluation.