MétaCan
Menu
Back to cohort
Record W4230268028 · doi:10.1016/s1931-5244(07)00028-x

Contents

2007· paratext· en· W4230268028 on OpenAlexaff
Mani Keshtgarpour, Arkadiusz Z. Dudek, Pascal Lapierre, Kathie Be, Fernando Álvarez, Que Montre ́al, Luca Miele, Alessandra Forgione, Antonio Gasbarrini, Antonio Grieco, Manuela G. Neuman, Jean‐Pierre Benhamou, Patrick Marcellin, Dominique Valla, Izabella M. Malkiewicz, Gad Katz, Cristhian Trepo, Marc Bourlière, Ross Cameron, Lawrence Cohen, Mary E. Morgan, Hemda Schmilovitz‐Weiss, Ziv Ben‐Ari, Samuele Nanni, Giovanni Melandri, Roeland Hanemaaijer, Vittorio Cervi, Luciana Tomasi, Annalisa Altimari, Natascha van Lent, Pierluigi Tricoci, Maria Letizia Bacchi Reggiani, Angelo Branzi, Timotej Jagrič, Marko Marhl, Dus ˇan Štajer, Špela Kocjanc, Tomaz ˇjagric ˇ, Matej Podbregar, Rui‐Xing Yin, Liang Wenwu, Jeffrey Laurence, Michael Franklin

Bibliographic record

VenueTranslational research · 2007
Typeparatext
Languageen
FieldMedicine
TopicCardiac Ischemia and Reperfusion
Canadian institutionsnot available
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.001
metaresearch head score (Gemma)0.004
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: Other · Consensus signal: Other
Teacher disagreement score0.637
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.6370.502

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 head0.156
GPT teacher head0.464
Teacher spread0.308 · 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
GenreOther

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
Published2007
Admission routes1
Has abstractno

Explore more

Same venueTranslational researchSame topicCardiac Ischemia and ReperfusionFrench-language works237,207