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Record W3083892901 · doi:10.1016/j.cyto.2020.155267

Cytokines and metabolic regulation: A framework of bidirectional influences affecting Leishmania infection

2020· review· en· W3083892901 on OpenAlexafffund
Neelam Bodhale, Mareike Ohms, Carolina Ferreira, Inês Mesquita, Arkajyoti Mukherjee, Sónia André, Arup Sarkar, Jérôme Estaquier, Tamás Laskay, Bhaskar Saha, Ricardo Silvestre

Bibliographic record

VenueCytokine · 2020
Typereview
Languageen
FieldMedicine
TopicResearch on Leishmaniasis Studies
Canadian institutionsUniversité LavalCentre hospitalier de l'Université Laval
FundersEuropean Regional Development FundFondation pour la Recherche MédicaleBundesministerium für Bildung und ForschungAgence Nationale de la RechercheCanada Research ChairsEuropean Society of Clinical Microbiology and Infectious DiseasesFundação para a Ciência e a TecnologiaDepartment of Biotechnology, Ministry of Science and Technology, India
KeywordsLeishmaniaImmune systemBiologyPhenotypeAmastigoteCell biologyHost (biology)MacrophageLeishmania majorMetabolic pathwayImmunologyMetabolismParasite hostingIn vitroGeneticsGeneBiochemistry

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.968
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.059
GPT teacher head0.368
Teacher spread0.309 · 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 teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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

Citations19
Published2020
Admission routes2
Has abstractno

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