UNNS Spectral Corpus Acquisition and Preparation Pipeline
=========================================================

1. Initial Objective
--------------------
The goal was to obtain a large-scale experimentally grounded spectral corpus suitable for:
- UNNS ladder extraction
- realizability analysis
- admissibility mapping
- structural phase tracking
- connectivity-margin evaluation
- cross-material transition analysis

The target corpus needed:
- dense ordered measurements
- multi-domain material diversity
- experimentally measured parameters
- sufficiently continuous trajectories for ladder construction


2. Source Identification
------------------------
A large spectral parameter database was identified and exported into:
    spectralparam_full.TXT

The export contains:
- material identifiers
- spectral parameter values
- material names
- source/model descriptors
- coordinate values (energy / wavelength-like axis)
- experimentally derived optical/spectral measurements

------------------------
The raw data source was the SciGlass database repository:

    https://github.com/epam/SciGlass

The relevant release assets were:

    Property.zip
    select.zip

From these, the database files were extracted:

    Property.mdb
    select.MDB

Property.mdb was used to inspect the property ontology, especially LISTPROP.
select.MDB was used to access the actual glass/material records.

The working export produced from select.MDB was:

    spectralparam_full.TXT

3. Validation of Export Integrity
---------------------------------
The exported TXT corpus was inspected to verify:
- rows contain real physical measurements
- material names are preserved
- coordinate ordering exists
- numeric continuity is present
- the export is not metadata-only
- the export is not schema-only
- the export is not a truncated preview

Representative materials confirmed:
- Mn3O4
- NiO
- Fe2O3
- ZnO
- La2O3
- B2O3
- YF3
- Dy2O3
- Er2O3
- V2O5
- PbF2

The export was confirmed to contain actual structured spectral measurements suitable for UNNS processing.


4. Structural Interpretation of the Corpus
------------------------------------------
The dataset was recognized as a naturally ordered spectral trajectory corpus.

Each material forms:
    coordinate → parameter trajectory

This structure is directly compatible with:
- ladder generation
- realizability-space embedding
- admissibility trajectory analysis
- margin evolution studies
- deformation tracking

The corpus was identified as especially valuable because:
- measurements are continuous
- trajectories are dense
- materials are physically diverse
- ordering is intrinsic to the data itself


5. Key Realization
------------------
It was determined that:
- MDB/database access is no longer necessary
- the TXT export alone is sufficient

The TXT corpus itself already contains:
- the ordering structure
- the physical measurements
- the spectral continuity
- the material segmentation

required for ladder extraction and UNNS analysis.


6. Planned Conversion Stage
---------------------------
A dedicated conversion engine was planned:

    spectral_ladder_generator.py

Purpose:
- parse spectralparam_full.TXT
- group rows by material
- sort rows by spectral coordinate
- extract ordered trajectories
- convert trajectories into UNNS-compatible ladders
- normalize outputs for STRUC-PERC-I ingestion


7. Planned Processing Flow
--------------------------
Intended processing sequence:

    spectralparam_full.TXT
        ↓
    material grouping
        ↓
    coordinate sorting
        ↓
    spectral trajectory extraction
        ↓
    ladder normalization
        ↓
    UNNS ladder generation
        ↓
    STRUC-PERC-I processing
        ↓
    phase mapping
        ↓
    admissibility analysis
        ↓
    connectivity-margin evaluation
        ↓
    structural regime classification


8. Scientific Motivation
------------------------
The corpus was identified as highly important for testing:

- interaction hierarchy
- connectivity-margin ordering
- structural boundary compression
- admissible clustering
- realizability geometry
- cross-domain universality
- transition topology
- regime persistence across material classes

The diversity of:
- oxides
- semiconductors
- borates
- fluorides
- dielectric materials
- metallic compounds

provides a strong basis for testing whether:
- admissibility structures
- margin laws
- and realizability geometry

remain stable across radically different physical systems.


9. Relation to Existing UNNS Theory
-----------------------------------
The corpus was recognized as strongly aligned with:
- Connectivity Margin as a Coordinate of Realizability Space
- The Margin-Confinement Law
- Interaction Unification manuscripts
- structural phase transition framework
- admissibility manifold formalism
- boundary-accessibility interpretation
- realizability trajectory analysis

The spectral corpus is expected to become:
- a condensed-matter realization corpus
- a transition-regime testbed
- and a large-scale validation domain
for UNNS realizability geometry.