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Record W7099915964

Jens von Bergmann (University of Calgary),

2010· article· en· W7099915964 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicPotassium and Related Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsSymplectic geometrySymplectomorphismMathematical proofDimension (graph theory)SPHERESSymplectic manifoldMoment map
DOInot available

Abstract

fetched live from OpenAlex

Symplectic manifolds are the natural domains of the modern mathematical formulation of classical mechanics, and they play a prominent role in many areas of mathematics. Since the introduction of the theory J–holomorphic curves by Gromov in [5], a tremendous amount of progress has been made in the study of these manifolds and the maps which preserve their symplectic structures. This progress has been particularly dramatic in the case of symplectic manifolds of dimension 4. For example, for S 2 ×S 2, the symplectic forms are classified (see [5], [14]), their symplectomorphism groups are well understood (see [5], [3]), and their Lagrangian spheres are all known to be symplectically equivalent (see [6]). Ruled symplectic 4–manifolds have also been completely classified (see [11]). The proofs of these results all have the same starting point; the existence of foliations by J–holomorphic spheres for all tamed almost complex structures. There have been several attempts to establish the existence of such foliations in more general settings. It was recently shown in [7] that such existence statements do not hold for foliations by J–holomorphic spheres of manifolds of dimension greater than 4. For index reasons, one can also not expect to find foliations by J–holomorphic curves of higher genus. To overcome this latter limitation, in the setting of symplectizations of a contact 3–manifolds, H. Hofer proposed in [8] to replace the standard J–holomorphic map equation with a parameterized version where the parameter takes values in the

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.572
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.004
GPT teacher head0.197
Teacher spread0.193 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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