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Record W2095901006 · doi:10.1109/tadvp.2009.2013454

Frequency-Division Bidirectional Communication Over Chip-to-Chip Channels

2009· article· en· W2095901006 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Advanced Packaging · 2009
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsUniversity of Toronto
FundersCMC MicrosystemsIntel Corporation
KeywordsTransmitterEmphasis (telecommunications)ChipElectronic engineeringChannel (broadcasting)Computer scienceFrequency dividerFilter (signal processing)Division (mathematics)SIGNAL (programming language)Electrical engineeringTelecommunicationsEngineeringCMOSMathematics

Abstract

fetched live from OpenAlex

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Frequency division multiple access is applied to bidirectional communication over chip-to-chip links. Frequency division is implemented by dividing the spectrum into low-frequency (dc) and high-frequency (ac) bands using a simple <emphasis emphasistype="italic">LC</emphasis> filter. The nonidealities that this filter introduces are compensated for with a transmitter/receiver pair that can recover signals in both bands. The receiver uses a dual-path topology that includes hysteresis to recover data from a signal with no dc content. The transmitter is a 6-tap (FIR) pre-emphasis equalizer with variable tap spacing. In simulation, the transmitter and receiver simultaneously communicate error-free at 8 Gb/s over the ac channel and at 500 Mb/s over the dc channel. Measurements shows that the ac and dc signals can be individually recovered and that the two signals occupy distinct frequency bands. </para>

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.845
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 head0.014
GPT teacher head0.263
Teacher spread0.249 · 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