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Record W2808262624 · doi:10.1016/j.jcmg.2018.03.019

Rationale and Design of the Strain Surveillance of Chemotherapy for Improving Cardiovascular Outcomes

2018· article· en· W2808262624 on OpenAlexafffund
Tomoko Negishi, Paaladinesh Thavendiranathan, Kazuaki Negishi, Thomas H. Marwick, Svend Aakhus, Klaus Murbræch, Richard J. Massey, Manish Bansal, Nobuaki Fukuda, Masaki Izumo, André La Gerche, Ben Costello, Julie Lemieux, Marc‐André Côté, Jonathan Deblois, Philip M. Mottram, Sakiko Miyazaki, Mark Nolan, Martin Pěnička, Tomáš Ondrúš, Evangelos Stefanidis, Stéphanie Seldrum, Mitra Shirazi, Evgeny Shkolnik, Eitan Amir, Babitha Thampinathan, Liza Thomas, Hirotsugu Yamada, Dragoş Vinereanu, Bogdan A. Popescu, Diana Mihalcea, Andreea Călin, Goo‐Yeong Cho, Koji Kurosawa, Maurizio Galderisi, Ciro Santoro

Bibliographic record

VenueJACC. Cardiovascular imaging · 2018
Typearticle
Languageen
FieldMedicine
TopicChemotherapy-induced cardiotoxicity and mitigation
Canadian institutionsToronto General HospitalUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsMedicineEjection fractionInternal medicineAnthracyclineCardiologyRandomized controlled trialHeart failureBreast cancerCardiotoxicityObservational studyChemotherapyClinical endpointIntensive care medicineCancer

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)0.024
metaresearch head score (Gemma)0.029
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.024
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.029
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.018
GPT teacher head0.248
Teacher spread0.230 · 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
GenreMethods

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

Citations139
Published2018
Admission routes2
Has abstractno

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