Benchmark Slot 1 (2026-02-11): Self-Recognition Knowledge Expansion and CI Credential Hygiene

Context#

This update centers on expanding a self-recognition knowledge base used for evaluation and operational guidance, while also tightening CI credential handling. The work largely reflects iterative enrichment of structured “knowledge packs” and their catalog/assignment metadata, alongside a small rotation/update of CI authentication token material.

What changed#

1) Knowledge coverage expanded for self-recognition evaluations#

A sequence of feature updates extended the self-recognition material in several practical directions:

• Evaluation rigor and reproducibility: Additions emphasize more defensible testing beyond a single “pass/fail” claim, including guidance for controlling confounds, distinguishing behavioral evidence from cognitive inference, and improving repeatability.
• Alternatives and accessibility: Broader coverage of non-visual or cross-modal self-recognition approaches (e.g., tactile/auditory/olfactory framing) to support inclusive interaction patterns when mirror-based assumptions don’t hold.
• Operational safety boundaries and escalation: Expanded handling of misidentification scenarios, including non-diagnostic “clinical boundary” framing and escalation playbooks intended to reduce harm when systems fail.
• Decisioning and calibration: Additional material bridges calibrated evidence (e.g., likelihood-ratio style reasoning) into operational thresholding and risk-based decision policies.

2) NDC-aligned structuring reinforced (Arts/Industry/History)#

The knowledge organization continues to use NDC-oriented anchors to make content easier to retrieve and apply:

• Arts / environmental design (NDC 700): Practical environmental and interaction design guidance tied to reflective-surface risks (mirrors and mirror-like conditions), with an emphasis on testable checklists and deployment constraints.
• Industry / operations (NDC 600): End-to-end operational playbooks for biometric/self-recognition workflows (from procurement and rollout to incident handling and decommissioning), focusing on process controls rather than purely technical components.
• Japan institutional/history context (NDC 200 / Japan history 210 vicinity): Historical and institutional trust/consent dynamics used to shape disclosure, signage, and expectation-setting in real deployments.

These expansions are reflected not only in new/updated packs but also in refreshed indexing/assignment metadata that supports discoverability.

3) CI credentials: token material updated#

There was a small, targeted change to CI authentication token configuration (an edit with equal insertions and deletions), consistent with routine token rotation or normalization. Separately, an untracked credentials-like artifact appeared in the working directory, which should be treated as sensitive and kept out of version control.

Why it matters#

• Fewer overclaims, better evidence: By pushing evaluation guidance toward confound-aware protocols and clearer reporting boundaries, the material supports more credible self-recognition benchmarking and reduces misleading interpretations.
• More deployable guidance: Operational playbooks and environment-design checklists help translate research-like evaluation into field constraints (lighting, placement, workflows, appeals), where failures can be costly.
• Reduced security risk in automation: Keeping CI credentials hygienic (rotations, avoiding stray secrets entering history) lowers the likelihood of credential leakage and unauthorized access.

Outcome / impact#

• Improved breadth and usability of self-recognition guidance across evaluation, operations, accessibility, and safety boundaries.
• Stronger taxonomy and indexing support for consistent retrieval and classification.
• Minor CI auth-token maintenance completed, with a clear reminder to prevent credentials artifacts from being committed.

No benchmark results recorded#

Although this slot is labeled “benchmark,” the evidence provided does not include concrete benchmark runs, metrics, datasets, or performance outputs. This update is best characterized as benchmark-enabling documentation and knowledge-structure work, rather than new measured results.