Why is EIT so hard, and what are we doing about it?
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 focus issue of Physiological Measurement follows the successful 15th International Conference on Biomedical Applications of Electrical Impedance Tomography (EIT 2014) held at the Glen House Resort in Gananoque, Ontario, Canada, from 24–26 April 2014. The conference was organized by Andy Adler, of the department of systems and computer engineering at Carleton University, in Ottawa, Canada, and co-organized by Bartłomiej Grychtol, of the Fraunhofer Project Group for Automation in Medicine and Biotechnology in Mannheim, Germany. A new award for best student paper was presented to Winkler et al (2014) and runner-up award to Dodd and Mueller (2014). \n \nThis continues the tradition of successful conferences on biomedical applications of electrical impedance tomography, as was the case with the 14th International Conference on Biomedical Applications of Electrical Impedance Tomography (EIT 2013), held on 22–25 April 2013 at Heilbad Heiligenstadt, Germany, and hosted by Uwe Pliquet of the Institut für Bioprozess- und Analysenmesstechnik. This year's conference is the 16th International Conference on Biomedical Applications of Electrical Impedance Tomography (EIT 2015) and is to be held in Neuchâtel, Switzerland on 2–5 June 2015, and hosted by Josep Solà and Fabian Braun of the Centre Suisse d'Électronique et de Microtechnique. This conference will be followed by a focus issue in Physiological Measurement that will be published in 2016. \n \nThis issue contains papers stemming from discussion and feedback during the 2014 conference, and is also an opportunity for new researchers to join the community and describe recent innovations. There were 77 accepted submissions (including three keynotes, 45 oral presentation and 29 posters). All authors were invited to prepare new peer-reviewed papers for inclusion in this issue of Physiological Measurement. Manuscripts were put through a process of careful review before selection, and 18 were accepted (of 27 submitted), covering an important range of topics.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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