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Record W2773478344 · doi:10.1155/2018/3546870

Corrigendum to “Low‐Level Laser Irradiation Exerts Antiaggregative Effect on Human Platelets Independently on the Nitric Oxide Metabolism and Release of Platelet Activation Markers”

2018· erratum· en· W2773478344 on OpenAlexaff
Piotr Rola, Adrian Doroszko, Ewa Szahidewicz-Krupska, Paweł Rola, Piotr Dobrowolski, Robert Skomro, Alicja Szymczyszyn, Grzegorz Mazur, Arkadiusz Derkacz

Bibliographic record

VenueOxidative Medicine and Cellular Longevity · 2018
Typeerratum
Languageen
FieldMedicine
TopicLaser Applications in Dentistry and Medicine
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsNitric oxidePlateletPlatelet activationChemistryBioavailabilityPlatelet-rich plasmaPharmacologyIrradiationMetabolismBiophysicsBiochemistryInternal medicineMedicineBiology

Abstract

fetched live from OpenAlex

Exerts Antiaggregative Effect on Human Platelets Independently on the Nitric Oxide Metabolism and Release of Platelet Activation Markers" [1], there was an error in the second affiliation where the name of the university was missing. The correct affiliation list is shown above.

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)0.003
metaresearch head score (Gemma)0.026
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: none
Teacher disagreement score0.062
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.026
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0620.053

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 head0.042
GPT teacher head0.298
Teacher spread0.257 · 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

Citations10
Published2018
Admission routes1
Has abstractyes

Explore more

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