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
4th World Congress on TeledermatologyTbilisi, Georgia, 4–6 October 2012The 4th World Congress of Teledermatology was held from 4–6 October 2012 at Tbilisi, Georgia. George Galdava from the Tbilisi State University, Tbilisi, Georgia and Oleg Kvlividze from the Institute of Dermatology and Venereology, Tbilisi, Georgia, were the Congress President and Secretary, respectively. The Congress theme of ‘dermatology conquering distance’ was exemplified by the speaker delegates from across the globe. Stella Atkins from the University of British Columbia, Canada, started the scientific session with her sterling talk on ‘Automated melanoma diagnosis using a dermoscope attached to a smart phone’. The role of NGOs in the establishing and promotion of telemedicine network today was stressed by Olga Litusi, from Ukraine. Saul Halpern of the British Teledermatology Society expressed that dermatologists in the UK appear to be gradually accepting Teledermatology. The American Academy of Dermatology, African Teledermatology Project was reviewed by Karen Mckoy Lahey Clinic, VT, USA. The concept of virtual hospital was elaborated by Leonard Witkamp from KSYOS TeleMedical Centre, the first virtual hospital in The Netherlands. In his presentation, he concluded that health management practice has been applied in the development, research and large scale implementation of teledermatology. The Indian delegates Jayakar Thomas from the Sree Balaji Medical College and Hospital (Chromepet, Chennai, India), Parimalam Kumar, Head of Dermatology (Thanjavur, India) and Dinesh Kumar from the KK CHILDS Trust Hospital (Nungambakkam, India) discussed the current status and the future directions of Teledermatology in India.
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) | 0.001 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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