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Record W2800277205 · doi:10.1007/s12017-018-8488-8

Neuroimmunologic and Neurotrophic Interactions in Autism Spectrum Disorders: Relationship to Neuroinflammation

2018· review· en· W2800277205 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNeuroMolecular Medicine · 2018
Typereview
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsNeuroinflammationAutismImmune systemNeuroscienceNeurotrophinImmune dysregulationAutism spectrum disorderNeurotrophic factorsPhenotypeNeurologyNeuroimmunologyPsychologyBiologyCentral nervous systemImmunologyReceptorGeneticsDevelopmental psychologyGeneInflammation

Abstract

fetched live from OpenAlex

Autism spectrum disorders (ASD) are the most prevalent set of pediatric neurobiological disorders. The etiology of ASD has both genetic and environmental components including possible dysfunction of the immune system. The relationship of the immune system to aberrant neural circuitry output in the form of altered behaviors and communication characterized by ASD is unknown. Dysregulation of neurotrophins such as BDNF and their signaling pathways have been implicated in ASD. While abnormal cortical formation and autistic behaviors in mouse models of immune activation have been described, no one theory has been described to link activation of the immune system to specific brain signaling pathways aberrant in ASD. In this paper we explore the relationship between neurotrophin signaling, the immune system and ASD. To this effect we hypothesize that an interplay of dysregulated immune system, synaptogenic growth factors and their signaling pathways contribute to the development of ASD phenotypes.

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.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.963
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.001

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 head0.100
GPT teacher head0.375
Teacher spread0.275 · 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