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Record W2908432470 · doi:10.1007/s10877-018-00242-3

Is the new ASNM intraoperative neuromonitoring supervision “guideline” a trustworthy guideline? A commentary

2019· letter· en· W2908432470 on OpenAlexaff
Stanley A. Skinner, Elif Ilgaz Aydınlar, Lawrence F. Borges, Bob S. Carter, Bradford L. Currier, Vedran Deletis, Charles Dong, John P. Dormans, Gea Drost, Isabel Fernández-Conejero, E. Matthew Hoffman, Robert N. Holdefer, Paulo André Teixeira Kimaid, Antoun Koht, Karl F. Kothbauer, David B. MacDonald, John J. McAuliffe, David E. Morledge, Susan H. Morris, Jonathan Norton, Klaus Novak, Kyung Seok Park, Joseph H. Perra, Julian Prell, David M. Rippe, Francesco Sala, Daniel M. Schwartz, Martín J. Segura, Kathleen Seidel, Christoph N. Seubert, Mirela V. Simon, Francisco Soto, Jeffrey A. Strommen, Andrea Szelényi, Armando Tello, Sedat Ulkatan, Javier Urriza, Marshall F. Wilkinson

Bibliographic record

VenueJournal of Clinical Monitoring and Computing · 2019
Typeletter
Languageen
FieldMedicine
TopicIntraoperative Neuromonitoring and Anesthetic Effects
Canadian institutionsUniversity of ManitobaUniversity of SaskatchewanDalhousie UniversityUniversity of British Columbia
FundersNorthwestern UniversityMassachusetts General HospitalScoliosis Research SocietyMayo Clinic
KeywordsGuidelineAnesthesiologyTrustworthinessMedicineIntensive care medicineMedical emergencyMedical physicsComputer scienceAnesthesiaComputer securityPathology

Abstract

fetched live from OpenAlex

Erratum in \n \n Correction to: Is the new ASNM intraoperative neuromonitoring supervision "guideline" a trustworthy guideline? A commentary. [J Clin Monit Comput. 2019] \n \nComment in \n \n Response to: Is the new ASNM intraoperative neuromonitoring supervision "guideline" a trustworthy guideline? A commentary. [J Clin Monit Comput. 2019] \n \nComment on \n \n Practice guidelines for the supervising professional: intraoperative neurophysiological monitoring. [J Clin Monit Comput. 2019]

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 imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.140
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.051
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.140
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.002
Science and technology studies0.0050.006
Scholarly communication0.0050.005
Open science0.0040.003
Research integrity0.0510.043
Insufficient payload (model declined to judge)0.0160.020

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.

Opus teacher head0.058
GPT teacher head0.402
Teacher spread0.344 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations5
Published2019
Admission routes1
Has abstractyes

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