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.
Bibliographic record
Abstract
This article describes the detailed efforts of the winning contribution of the first student competition in microwave transistor modeling, held at the 2012 International Microwave Symposium (IMS2012) in Montreal, Quebec, Canada. The competition was sponsored by MTT-1, Freescale Semiconductor Inc., and WIN Semiconductor Inc. The transistor modeled was a commercially available high-power device from Freescale, and the characterization data required for modeling was distributed to all competitors. No measurements were to be carried out by the participants, so all students world wide, even those without expensive transistor characterization equipment, could participate. The main objectives of the competition were to identify the technology and develop a nonlinear model from the provided measurement data set [e.g., cold field effect transistor (FET) measurements, pulsed IV, IV versus temperature, S parameter versus bias, and pulsed S-parameter measurements]. The developed model was also to be validated versus large signal one- and two-tone measurements. The validation data was in the form of output power and power added efficiency (PAE) versus input power and measured at two different conditions, e.g., input/output terminations for maximum efficiency and maximum output power, respectively. An accurate model should be able to predict the large signal measurements across the full range of input power levels and bias points available. The judgment of the modeling result was based on the agreement between model simulation and measurement in terms of output power, efficiency, and third-order intermodulation (IM3) versus input power, several of which were not provided to the competitors.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.009 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it