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Record W2295021757 · doi:10.1049/iet-cds.2014.0335

Holistic design strategy for high‐selectivity low‐loss integrated millimetre‐wave image‐reject filters

2015· article· en· W2295021757 on OpenAlex
Mury Thian, Vincent Fusco

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIET Circuits Devices & Systems · 2015
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsnot available
FundersQueen's UniversityQueen's University Belfast
KeywordsFilter (signal processing)Electronic engineeringResonatorPrototype filterTransmission (telecommunications)m-derived filterMaterials scienceOpticsFilter designAcousticsComputer scienceElectrical engineeringOptoelectronicsEngineeringTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

To alleviate practical limitations in the design of millimetre‐wave on‐chip image‐reject filters, systematic design methodologies are presented. Three low‐order filters with high‐selectivity and low‐loss characteristics are designed and compared. Transmission zeroes are created by means of a quarter‐wave transmission line (filter 1) and a series LC resonator (filters 2 and 3). Implemented on silicon germanium, the filters occupy 0.125, 0.064 and 0.079 mm 2 chip area including pads. The measured transmission losses across 81–86 GHz E‐band frequency range are 3.6–5.2 dB for filter 1, 3.1–4.7 dB for filter 2 and 3.6–5 dB for filter 3 where rejection levels at the image band are >30 dB.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.855
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.065
GPT teacher head0.255
Teacher spread0.190 · 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