MétaCan
Menu
Back to cohort
Record W4246740821 · doi:10.17771/pucrio.acad.31668

AUTOMATIC HIGH-DYNAMIC AND HIGH-RESOLUTION PHOTON COUNTING OTDR FOR OPTICAL FIBER NETWORK MONITORING

2017· dissertation· en· W4246740821 on OpenAlexaff
Felipe Calliari

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicAdvanced Optical Sensing Technologies
Canadian institutionsOptech (Canada)
Fundersnot available
KeywordsOptical time-domain reflectometerOptical fiberHigh resolutionComputer scienceFiberMaterials scienceOptoelectronicsPhysicsOpticsFiber optic sensorFiber optic splitterRemote sensingGeology

Abstract

fetched live from OpenAlex

[pt] Neste trabalho é apresentado o desenvolvimento de uma estrutura automatizada para o monitoramento de fibras ópticas. Esta estrura consite em dois tipos de reflectômetros ópticos por contagem de fótons no domínio do tempo e um filtro de tendências que é utilizado para detectar as falhas em uma fibra óptica de forma automatizada. O primeiro OTDR por contagem de fótons apresenta uma faixa dinâmica de 32 dB com resolução espacial de 6 m, já o segundo OTDR apresenta uma faixa dinâmica de 14 dB e uma resolução de 3 cm. Foi demonstrada a sua capacidade de detectar falhas automaticamente em um enlace óptica e de sintonização no monitoramento de redes passivas WDM.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.874
Threshold uncertainty score1.000

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)0.0000.000

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 head0.010
GPT teacher head0.279
Teacher spread0.269 · 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 designOther design
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

Citations4
Published2017
Admission routes1
Has abstractyes

Explore more

Same topicAdvanced Optical Sensing TechnologiesFrench-language works237,207