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
in Kuala Lumpur, Malaysia.It is a tremendous honor for the Cambridge Innovation Center (Singapore) to serve as the collaborative institution to enhance collaboration and mutually develop for being an international platform.ICLRC 2024 focuses on high quality presentations and papers that address contemporary issues on fundamental research leading to new methods, or adaptation of existing methods for new applications related to the topics of language studies and cultural communication.It aims to deliver an outstanding global forum for academics, researchers, scientists, engineers, students in the world to link up, exchange information and discussion.The conference has 6 keynote speeches and 9 invited speeches in total, and it has drawn about 120 delegates from 9 countries (China, India, Canada, United Kingdom, United States, Singapore, Malaysia, Australia, Philippines).The conference comprised a diverse spectrum of highly technical presentations by keynote and invited speaker sessions and authors of submitted papers.We are pleased to present the SHS Web of Conferences of the ICLRC 2024 and we sincerely hope that all participants and interested readers would be benefited from this proceedings.We want to express our heartfelt appreciation to our contributors, sponsors, colleagues and associations that helped make this conference successful.We'd also want to thank everyone on the committees and editorial board for the assistance and feedback.
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 | 0.001 | 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) | 0.002 | 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