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
Transactions are fundamental components of an economy. This paper presents an analytic apparatus that can be used to analyze transaction data, where the transaction is the fundamental unit of observation. Transactions also are a potentially fundamental observation associated with the detection and characterization of organizational activities and events through acquisitions, trades or financial transactions. The objective of the research described in this paper was to develop a mathematical signature that represents transaction data (Point A to Point B, etc.), and visualize the transactions using currently available visualization tools. The representational signature should be useful for indicating change in organizational behavior, and for indicating when anomalous behavior occurs, i.e., something that is different than the common daily, quarterly or annual occurrence. The mathematical construct will be the same whether the transactions are country trade data or bank transactions, electrical grid transactions or some other multi-point transfer of information, asset, action, etc. The particular data example shown in this paper is international economic trade data for six countries; Mexico and its 5 largest trading partners, the United States, Germany, Canada, Japan and South Korea.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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