NHOP: A Nested Associative Pattern for Analysis of Consensus Sequence Ensembles
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this research, we introduce a novel, complex associative pattern that is found to be very useful because it identifies the core associative structure from the data. We refer to it as nested high-order pattern. The pattern is more specific than associative patterns represented as multiple variables. It also generalizes sequential patterns, as the outcomes need not be contiguous. This paper outlines two search algorithms, the $(r)$-Tree and Best-$(k)$ algorithm in its detection. It was then applied to an analysis of biomolecule using the aligned sequence family of the molecule. In the SH3 protein, a model for protein-protein interaction mediator, we identify functional groups (core and binding sites) in the three-dimensional structure as well as amino acid patterns dominating certain species.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it