📄

Paper

Functional connectivity-based prediction of Autism on site harmonized ABIDE dataset

by Independent / Community 00183500ec8f4bf5bbbca2063f958ad4925817c1

Free2AITools Nexus Index

69.8

S: Semantic 50

Query-time baseline · scored live at search

A: Authority 86

P: Popularity 63

R: Recency 100

Q: Quality 65

Tech Context

Vital Performance —

Objective: The larger sample sizes available from multi-site publicly available neuroimaging data repositories makes machine-learning based diagnostic classification of mental disorders more feasible by alleviating the curse of dimensionality. However, since multi-site data are aggregated post-hoc, i.e. they were acquired from different scanners with different acquisition parameters, non-neural inter-site variability may mask inter-group differences that are at least in part neural in origin....

Source →

Semantic Scholar 87 Citations

Paper Information Summary
Entity Passport
Registry ID	00183500ec8f4bf5bbbca2063f958ad4925817c1
License	ArXiv
Provider	semantic_scholar

📜

Cite this paper

Academic & Research Attribution

BibTeX

@misc{00183500ec8f4bf5bbbca2063f958ad4925817c1,
  author = {Unknown},
  title = {Functional connectivity-based prediction of Autism on site harmonized ABIDE dataset Paper},
  year = {2026},
  howpublished = {\url{https://api.semanticscholar.org/00183500ec8f4bf5bbbca2063f958ad4925817c1}},
  note = {Accessed via Free2AITools.}
}

APA Style

Unknown. (2026). Functional connectivity-based prediction of Autism on site harmonized ABIDE dataset [Paper]. Free2AITools. https://api.semanticscholar.org/00183500ec8f4bf5bbbca2063f958ad4925817c1

🔬Technical Deep Dive

Full Specifications [+]

⚖️ Free2AITools Nexus Index V2.0

Methodology How FNI works

Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 86

Popularity (P) 63

Recency (R) 100

Quality (Q) 65

💬 Index Insight

FNI V2.0 for Functional connectivity-based prediction of Autism on site harmonized ABIDE dataset: Authority (A:86), Popularity (P:63), Recency (R:100), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology

Open data Updated: Live data

📝 Executive Summary

"Objective: The larger sample sizes available from multi-site publicly available neuroimaging data repositories makes machine-learning based diagnostic classification of mental disorders more feasible by alleviating the curse of dimensionality. However, since multi-site data are aggregated post-hoc, i.e. they were acquired from different scanners with different acquisition parameters, non-neural inter-site variability may mask inter-group differences that are at least in part neural in origin...."

❝ Cite Node

@article{Unknown2026Functional,
  title={Functional connectivity-based prediction of Autism on site harmonized ABIDE dataset},
  author={},
  note={Indexed by Free2AITools},
  year={2026}
}

🔗 Full Paper

Free2AITools indexes the abstract and factual metadata for this paper. Read the complete, authoritative paper on the official source.

Read the full paper on arXiv

📊 Research Signals

📈87CitationsSemantic Scholar

🏛️86AuthorityFNI pillar

⏱️100RecencyFNI pillar

✅65QualityFNI pillar

🗂️vision multimediaField

📦Data Source: semantic_scholar

🔄 Updated daily

Source summary: Based on semantic_scholar metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹ️ Verify with original source

🛡️ Paper Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

source: semantic_scholar
author: Unknown
license: ArXiv
tags: paper, research, academic

⚙️ Technical Specs

architecture: null
params billions: null
context length: null
pipeline tag

📊 Engagement & Metrics

downloads: 0
stars: null
forks: null
citations: 87

Data indexed from public sources. Updated daily.