MedTranscripts - A multimodal dataset of Spanish medical videos and time-aligned transcripts
Bibliographic record
Abstract
MedTranscripts is a dataset of 30 hours of medical videos and audios in Spanish, time-aligned with the corresponding transcripts. Videos were obtained from authorized medical providers online. It contains the following data: A gold standard of 20 hours of 290 videos and audios, each revised by two human annotators. A silver standard of 10 hours of 76 videos and audios, in which only the medical transcripts were each revised by a single annotator. A pronunciation dictionary of medical words in Spanish, to be used with Montreal Forced Aligner. The dataset contains recordings from a total of 403 different speakers (200 male and 203 female). This repository contains only the audios and transcripts. Please, contact the author to get the corresponding videos. Acknowledgements The following linguists who contributed their time to revise and align the text and speech data of the dataset: Lara Alonso Álvaro Arozarena Miriam Lim Federico Ortega Adrián Ruiz Minnie Zheng
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.001 |
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 teacher head, 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".