Reply to the Commentary on “An appraisal of neostigmine versus sugammadex for neuromuscular blockade reversal in patients with a prior heart transplant”
Bibliographic record
Abstract
AMA Paredes S, Torres V, Chaves-Cardona H, Porter SB, Renew J. Reply to the Commentary on “An appraisal of neostigmine versus sugammadex for neuromuscular blockade reversal in patients with a prior heart transplant”. Anaesthesiology Intensive Therapy. 2023. doi:10.5114/ait.2023.130640. APA Paredes, S., Torres, V., Chaves-Cardona, H., Porter, S. B., & Renew, J. (2023). Reply to the Commentary on “An appraisal of neostigmine versus sugammadex for neuromuscular blockade reversal in patients with a prior heart transplant”. Anaesthesiology Intensive Therapy. https://doi.org/10.5114/ait.2023.130640 Chicago Paredes, Stephania, Vivian Hernandez Torres, Harold Chaves-Cardona, Steven B Porter, and Johnathan Ross Renew. 2023. "Reply to the Commentary on “An appraisal of neostigmine versus sugammadex for neuromuscular blockade reversal in patients with a prior heart transplant”". Anaesthesiology Intensive Therapy. doi:10.5114/ait.2023.130640. Harvard Paredes, S., Torres, V., Chaves-Cardona, H., Porter, S., and Renew, J. (2023). Reply to the Commentary on “An appraisal of neostigmine versus sugammadex for neuromuscular blockade reversal in patients with a prior heart transplant”. Anaesthesiology Intensive Therapy. https://doi.org/10.5114/ait.2023.130640 MLA Paredes, Stephania et al. "Reply to the Commentary on “An appraisal of neostigmine versus sugammadex for neuromuscular blockade reversal in patients with a prior heart transplant”." Anaesthesiology Intensive Therapy, 2023. doi:10.5114/ait.2023.130640. Vancouver Paredes S, Torres V, Chaves-Cardona H, Porter S, Renew J. Reply to the Commentary on “An appraisal of neostigmine versus sugammadex for neuromuscular blockade reversal in patients with a prior heart transplant”. Anaesthesiology Intensive Therapy. 2023. doi:10.5114/ait.2023.130640.
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 | 0.000 | 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 | 0.001 |
| 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 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".