Minimal immersions of compact bordered Riemann surfaces with free boundary
Bibliographic record
Abstract
Let N N be a complete, homogeneously regular Riemannian manifold of dim N ≥ 3 N \geq 3 and let M M be a compact submanifold of N N . Let Σ \Sigma be a compact orientable surface with boundary. We show that for any continuous f : ( Σ , ∂ Σ ) → ( N , M ) f: \left ( \Sigma , \partial \Sigma \right ) \rightarrow \left ( N, M \right ) for which the induced homomorphism f ∗ f_{*} on certain fundamental groups is injective, there exists a branched minimal immersion of Σ \Sigma solving the free boundary problem ( Σ , ∂ Σ ) → ( N , M ) \left ( \Sigma , \partial \Sigma \right ) \rightarrow \left ( N, M \right ) , and minimizing area among all maps which induce the same action on the fundamental groups as f f . Furthermore, under certain nonnegativity assumptions on the curvature of a 3 3 -manifold N N
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".