MétaCan
Menu
Back to cohort
Record W38971350 · doi:10.1016/j.fsi.2024.109738

Classification associative basée sur le Boosting.

2010· book-chapter· en· W38971350 on OpenAlexfundno aff
Emna Bahri, Stéphane Lallich

Bibliographic record

VenueEGC eBooks · 2010
Typebook-chapter
Languageen
FieldComputer Science
TopicImage Retrieval and Classification Techniques
Canadian institutionsnot available
FundersNational Institute for Health and Care ResearchInternational Development Research Centre
KeywordsBoosting (machine learning)Associative propertyComputer scienceArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

Antimicrobial peptides (AMPs) are an alternative to antibiotics for treatment and prevention of infections with a lower risk of bacterial resistance. Pituitary adenylate cyclase activating polypeptide (PACAP) is an outstanding AMP with versatile effects including antimicrobial activity and modulation of immune responses. The objective of this research was to study PACAP immunomodulatory effect on rainbow trout cell lines infected with Aeromonas salmonicida. PACAP from Clarias gariepinus (PACAP1) and a modified PACAP (PACAP5) were tested. RT-qPCR results showed that il1b and il8 expression in RTgutGC was significantly downregulated while tgfb expression was upregulated after PACAP treatment. Importantly, the concentration of IL-1β and IFN-γ increased in the conditioned media of RTS11 cells incubated with PACAP1 and exposed to A. salmonicida. There was a poor correlation between gene expression and protein concentration, suggesting a stimulation of the translation of IL-1β protein from previously accumulated transcripts or the cleavage of accumulated IL-1β precursor. In-silico studies of PACAP-receptor interactions showed a turn of the peptide characteristic of PACAP-PAC1 interaction, correlated with the higher number of interactions observed with this specific receptor, which is also in agreement with the higher PACAP specificity described for PAC1 compared to VPAC1 and VPACA2. Finally, the in silico analysis revealed nine amino acids related to the PACAP receptor-associated functionality.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.817
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.092
GPT teacher head0.245
Teacher spread0.153 · 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 designTheoretical or conceptual
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
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueEGC eBooksSame topicImage Retrieval and Classification TechniquesFrench-language works237,207