TACTILE GEIGER COUNTER FOR UBIQUITOUS COMPUTING
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
Firstly and most importantly I would like to thank Professor Stephen Brewster for guiding me through this dissertation, for all the advice, phones and resources he lent me and for giving me the opportunity to work on a project that nobody else has really done before. I would very much like to thank Andrew Crossan for regularly diagnosing and fixing my slightly fickle and temperamental SHAKE module, as well as Mark McGill and Andrew Ramsay for giving me the all the code I needed to get started on my project. Thanks also to Eve Hoggan for helping me to create and produce the vibration patterns used and Tony McBryan for lending me the SHAKE-compatible Anycom USB-200 Bluetooth dongle. It will be returned in one piece. Page | 2Summary Many studies have been carried out on using mobile devices and location-based technology such as digital compasses and Global Positioning Systems for the purposes of locating, extracting or navigating towards virtual targets in 3-dimensional space. There have been significant successes in showing that users can accurately orient towards and locate virtual items when the existence of these items is known, often having access to only audio or tactile
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 | 0.000 |
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