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
Voltage collapse is a phenomenon where voltage collapses at one or more busses due to lack of reactive power characterized by a decrease in voltage with increase in reactive power injection and voltage drop in connected lines due to large power flows. Bus-wise power balance equations, solved using the Newton- Raphson (NR) technique, are widely used to analyze power systems for VC. While bus-wise power balance equations succinctly model a power system, it and its Jacobian do not readily point out the most critical set of lines without additional analysis. In this paper, first, a line-wise set of equations for modeling a power system and its solution method using the NR technique for power flow analysis are proposed. Study results on 6-, 14-, 57-, and 118-bus IEEE systems, a 582-bus real system, 2383-bus Polish power system, and 9241-bus PEGASE system show that the proposed method is accurate, provides monotonic convergence, scales well of large systems, and is consistently faster up to twice the speed of the bus-wise NR method, while using sparse matrices. Second, a line-wise VC index is derived and shown to be directly present in the Jacobian of the line-wise NR method, identifying the susceptible set of lines without additional computation. Usefulness of VC index as an online VC assessment tool is demonstrated for a critical loading condition on test systems.
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 | 0.000 | 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