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Record W3199297159 · doi:10.1016/j.jpra.2021.09.001

Letter to the Editor: The Case for Publicly Funded Headache Surgery in Germany

2021· letter· en· W3199297159 on OpenAlexaff
Leonard Knoedler, Christian Chartier, Hassan ElHawary, Andreas Kehrer, Thomas Muehlberger

Bibliographic record

VenueJPRAS Open · 2021
Typeletter
Languageen
FieldMedicine
TopicMigraine and Headache Studies
Canadian institutionsMcGill University Health CentreMcGill University
Fundersnot available
KeywordsGermanReimbursementMedicineGeneral surgeryHealth careHealthcare systemSurgeryPolitical scienceHistory

Abstract

fetched live from OpenAlex

Headache surgery has become a considerable therapeutic option in headache treatment and is of rising interest in the German medical sector. This viewpoint outlines the need for reimbursement of headache surgery in the German healthcare system and demonstrates its cost-effectiveness. Using state-of-the-art patient selection algorithms, the authors found headache surgery to be cost-effective within 7.2 to 6.3 years. Of note, the approach presented is not limited to the German healthcare system.

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)0.002
metaresearch head score (Gemma)0.021
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 score0.015
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0150.010
Insufficient payload (model declined to judge)0.0040.002

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 head0.105
GPT teacher head0.354
Teacher spread0.249 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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