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This preprint reports a locally frozen 12,160-trial black-box evaluation of prompt-conditioned Arabic–Hebrew hybrid artifact formation in the dated gpt-5.4-2026-03-05 Chat Completions endpoint. The study comprises 10,240 primary trials across two exact system conditions and every integer output-token ceiling from 1 through 1,024, plus 1,920 frozen control and ablation trials. Classification used exact, untrimmed, unnormalized provider-returned UTF-8 bytes and logical code-point order. The primary census observed 7,253 exact assigned artifacts (70.8301%) and 7,293 mixed-script outputs (71.2207%). The dotted condition produced 4,830/5,120 exact T1 artifacts (94.3359%), while the undotted condition produced 2,423/5,120 exact T0 artifacts (47.3242%). Every exact artifact matched the dotted-versus-undotted identity assigned by its system condition, yielding 7,253/7,253 prompt-congruent exact outputs. The prospectively fixed pooled exact-rate threshold was not met because its Wilson lower bound was 69.9420%, while the prompt-congruence threshold was met with a Wilson lower bound of 99.9471%. The study further documents a 47.0117-percentage-point dotted–undotted rate difference, complete control and ablation results, token-ceiling trajectories, discovery-versus-replication divergence, Unicode morphology, and full operational-error accounting. A separately implemented verifier reconstructed all 12,160 retained attempt records and replayed 24,323 hash-chained events with zero classifier disagreements, no chain breaks, and no missing terminal slots. The findings establish a reproducible, code-point-specific black-box behavioral object and identify the dotted condition as the stable branch in the tested execution window, without claiming an internal mechanism, causality, intention, training-data provenance, or cross-vendor generality.

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