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Record W4283382224 · doi:10.3390/pathogens11070716

Integrating the Gut Microbiome and Stress-Diathesis to Explore Post-Trauma Recovery: An Updated Model

2022· article· en· W4283382224 on OpenAlexaff
Manasi Murthy Mittinty, Joshua Lee, David M. Walton, Emad El‐Omar, James M. Elliott

Bibliographic record

VenuePathogens · 2022
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsWestern University
Fundersnot available
KeywordsDiathesisMicrobiomePsychological interventionMedicineIntensive care medicineTraumatic injuryAdverse effectBioinformaticsPsychiatryImmunologyBiologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

Musculoskeletal conditions of traumatic and non-traumatic origin represent an ongoing health challenge. While the last three decades have seen significant advancement in our understanding of musculoskeletal conditions, the mechanisms of a delayed or lack of recovery are still a mystery. Here, we present an expansion of the integrated stress-diathesis model through the inclusion of the gut microbiome. Connecting the microbiome with known adverse neurobiologic, microbiologic and pathophysiologic sequelae following an injury, trauma or stressful event may help improve our knowledge of the pathogenesis of poor recovery. Such knowledge could provide a foundation for the exploration and development of more effective interventions to prevent the transition from acute to chronic pain.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.781
Threshold uncertainty score0.565

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
Research integrity0.0000.000
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 head0.033
GPT teacher head0.281
Teacher spread0.247 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations9
Published2022
Admission routes1
Has abstractyes

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