Bibliographic record
Abstract
The International Conference on Novel approaches and Developments in Biomedical Engineering (ICNADBE 2021) was held from 22 April 2021 to 23 April 2021. Due to the outbreak of COVID-19, this year’s conference was organized as fully virtual conference from Karunya Institute of Technology and Sciences, Coimbatore, India, through meeting system “Zoom”. In order to prepare ICNADBE 2021, the organizing committees, reviewers, session chairs as well as all the authors and presenters have made a lot of efforts and contributions. Thank you very much for always being supportive to the conference. We could not have pulled off this convention without all of your hard work and dedication. ICNADBE 2021 was consisted of 6 keynote speeches, Dr.Simona Badilesu, a senior Scientist from Cancordia University,Montreal, Canada,Dr.V.Suryanarayanan,a Scientist from CSIR,CECRI ,an Industrialist from Bangalore and four more eminent Academicians from India delivered keynote address on advances in Biomedical field.Each keynote speech lasted for 45min including 5min for Q&A, while for the authors’ presentation, 15min including Q&A was allocated. All participant were active, questions raised after every talk. The whole conference was held online in ZOOM, we also had a test run for each presenters in advance to ensure the success of delivery of the conference. For those who had internet problem, we also accepted a pre-recorded video presentation as an alternative of online presentation. ICNADBE 2021 aims to become premier international conference for in-depth discussion on the most-up-to-date and innovative ideas, research projects and practices in the field of biomedical engineering and medical devices. Papers published in the ICNADBE 2021 proceedings cover various topics from biomedical and instrumentation engineering to bio nanomaterials science as well as a broad range of related interdisciplinary subjects. List of EXECUTIVE COMMITTEE, ADVISORY COMMITTEE, KEYNOTE SPEAKERS are available in this pdf.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.549 | 0.411 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".