Corrections to finite-size scaling in the φ4 model on square lattices
Bibliographic record
Abstract
Corrections to scaling in the two-dimensional (2D) scalar [Formula: see text] model are studied based on nonperturbative analytical arguments and Monte Carlo (MC) simulation data for different lattice sizes L ([Formula: see text]) and different values of the [Formula: see text] coupling constant [Formula: see text], i.e. [Formula: see text], 1, 10. According to our analysis, amplitudes of the nontrivial correction terms with the correction–to–scaling exponents [Formula: see text] become small when approaching the Ising limit ([Formula: see text]), but such corrections generally exist in the 2D [Formula: see text] model. Analytical arguments show the existence of corrections with the exponent [Formula: see text]. The numerical analysis suggests that there exist also corrections with the exponent [Formula: see text] and, perhaps, also with the exponent about [Formula: see text], which are detectable at [Formula: see text]. The numerical tests provide an evidence that the structure of corrections to scaling in the 2D [Formula: see text] model differs from the usually expected one in the 2D Ising model.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".