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
Generalized Frequency Division Multiplexing (GFDM) is a multi-domain communication scheme where data symbols are transmitted over a time-frequency block. Tensors, which are multi-way arrays, can be efficiently used to model such systems. This paper presents a system model for a multiple input multiple output (MIMO) GFDM system using the Einstein product of tensors. The input and output are modelled as order 3 tensors where the three modes correspond to space, time and frequency domains. The equivalent channel between the input and output obtained from a cascade of transmit filter, physical channel and receive filter, is defined as an order 6 tensor which takes into account interference across all the domains. An information theoretic analysis of such a tensor channel is presented which is then used to develop a tensor based precoding scheme for MIMO GFDM systems. The effect of various GFDM pulse shape parameters on the capacity of the equivalent channel is explored. A multi-linear minimum mean square error (MMSE) receiver using the tensor framework is also presented.
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) | 0.000 | 0.000 |
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.
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