MétaCan
Menu
Back to cohort
Record W17764271 · doi:10.1063/1.2759489

Enforcing Security Policies on Programs

2006· article· en· W17764271 on OpenAlexaff
Hakima Ould‐Slimane, Mohamed Mejri, Kamel Adi

Bibliographic record

VenueNew Trends in Software Methodologies, Tools and Techniques · 2006
Typearticle
Languageen
FieldComputer Science
TopicSecurity and Verification in Computing
Canadian institutionsUniversité du Québec en OutaouaisUniversité Laval
Fundersnot available
KeywordsComputer scienceAutomatonRewritingProperty (philosophy)Symbolic executionSecurity policyProgramming languageEnforcementProgram analysisEmbeddingTheoretical computer scienceOperator (biology)Computer securitySoftware

Abstract

fetched live from OpenAlex

The efficiency and directedness of resonance energy transfer, by means of which electronic excitation passes between molecular units or subunits, fundamentally depend on the spectral features of donor and acceptor components. In particular, the flow of energy between chromophores in complex energy harvesting materials is crucially dependent on a spectral overlap integral reflecting the relative positioning and shapes of the absorption and fluorescence bands. In this paper, analytical results for this integral are derived for bands of Gaussian and log normal line shape; the methods also prove applicable to double Gaussian curves under suitable conditions. Underlying principles have been ascertained through further development of theory, with physically reasonable assumptions. Consideration of the Gaussian case, widely applicable to spectra of symmetric form, reveals that the directional efficiency of energy transfer depends equally on a frequency shift characterizing the spectroscopic gradient and the Stokes shift. On application to tryptophan residues, calculations based on a minimal parameter set give excellent agreement with experiment. Finally, an illustrative application highlights the critical role that the spectroscopic gradient and Stokes shift can exercise in extended, multichromophore energy harvesting 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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.849
Threshold uncertainty score0.842

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.144
GPT teacher head0.369
Teacher spread0.225 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations2
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueNew Trends in Software Methodologies, Tools and TechniquesSame topicSecurity and Verification in ComputingFrench-language works237,207