Preclinical and Clinical Studies Targeting Therapeutic Hypothermia in Cerebral Ischemia and Stroke
Bibliographic record
Abstract
Therapeutic Hypothermia and Temperature ManagementVol. 3, No. 1 Expert Panel DiscussionsPreclinical and Clinical Studies Targeting Therapeutic Hypothermia in Cerebral Ischemia and StrokeModerator: Patrick Lyden, Participants: Fred Colbourne, Patrick Lyden, and Stefan SchwabModerator: Patrick LydenDepartment of Neurology, Cedars-Sinai Medical Center, Los Angeles, California.Search for more papers by this author, Participants: Fred ColbourneCenter for Neuroscience, Department of Psychology, University of Alberta, Alberta, Canada.Search for more papers by this author, Patrick LydenDepartment of Neurology, Cedars-Sinai Medical Center, Los Angeles, California.Search for more papers by this author, and Stefan SchwabDepartment of Neurology, University of Erlangen-Nurnberg, Erlangen, Germany.Search for more papers by this authorPublished Online:13 Mar 2013https://doi.org/10.1089/ther.2013.1500AboutSectionsView articleView Full TextPDF/EPUB ToolsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View articleFiguresReferencesRelatedDetailsCited byProtecting the ischaemic penumbra as an adjunct to thrombectomy for acute stroke19 April 2018 | Nature Reviews Neurology, Vol. 14, No. 6 Volume 3Issue 1Mar 2013 InformationCopyright 2013, Mary Ann Liebert, Inc.To cite this article:Moderator: Patrick Lyden, Participants: Fred Colbourne, Patrick Lyden, and Stefan Schwab.Preclinical and Clinical Studies Targeting Therapeutic Hypothermia in Cerebral Ischemia and Stroke.Therapeutic Hypothermia and Temperature Management.Mar 2013.3-6.http://doi.org/10.1089/ther.2013.1500Published in Volume: 3 Issue 1: March 13, 2013PDF download
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.006 |
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 source (direct Gemma or distilled Codex), 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".