Bibliographic record
Abstract
exponential, 78 greedy, 39, 82 list, 82 of Dijkstra, 42 of Kruskal, 38 polynomial, 77 priority rule, 82 pseudo-polynomial, 77 allocation of resources, 1 altitude suite, 158 arc, 36 arc routing problem, 165 articulation point, 35 Augment-Merge algorithm, 184 B backtracking, 92 basic solution, 7 basic variables, 7 basis, 7 Benders' decomposition, 160 binary variable, 22 branch and bound, 90 branch and bound procedure, 91 bombardier flexjet, 159 branch and bound, 253 C canadian national railway, 159 canonical form, 5 capacity constraints, 170, 183 chain, 33 alternating, 46 augmenting, 47 closed, 33 elementary, 33 simple, 33 Cheapest Insertion algorithm, 167 Chinese postman problem, 174 Christofides' algorithm, 168 circuit, 36 Clarke and Wright's algorithm, 171 class NP, 78 class P, 79 clique, 32, 246, 249 coloring minimum, 247 column generation, 138, 148, 159 complementary slack, 13 complexity, 27, 249 connected component, 34 constraints, 1 convex hull, 21 complexity, 77 algorithmic, 77, 98 covering tour,
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.
How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.033 | 0.109 |
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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".