MétaCan
Menu
← Back to cohort
Record W2087448080 · doi:10.1117/12.2024296

Ultrafast transient characteristics of photoconductive elements for optical wireless communications

2013· article· en· W2087448080 on OpenAlexaff
Xian‐Min Jin, Christopher M. Collier, Jamieson J. A. Garbowski, Brandon Born, Jonathan F. Holzman

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2013
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsUltrashort pulsePhotoconductivityOptoelectronicsPhotocurrentPicosecondOptical switchOptical wirelessMaterials scienceTransient (computer programming)BiophotonicsSemiconductorOptical wireless communicationsWirelessComputer scienceOpticsVisible light communicationLaserPhysicsPhotonicsTelecommunicationsLight-emitting diode

Abstract

fetched live from OpenAlex

An integrated photoconductive (PC) sensor is introduced as an optoelectronic element for visible light optical wireless communications (OWC) links. The sensor applies the standard PC switch, being a biased metal-semiconductor-metal gap, in a three-fold-symmetric corner-cube architecture with a summed output photocurrent at the vertex. Such a form facilitates bidirectional retroreflective communications to meet fundamental OWC requirements for broad directional and broad spectral capabilities. The ultimate OWC capability, for ultrafast optoelectronic switching times, is studied here for material response and transit time response, and it is shown that ultrafast (picosecond) optoelectronic switching times can be achieved and the general device design consideration is discussed for emerging visible light OWC 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0040.001

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.

Opus teacher head0.015
GPT teacher head0.238
Teacher spread0.222 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE→Same topicPhotonic and Optical Devices→French-language works237,207→