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Record W3157466239 · doi:10.14288/1.0397005

Why biomedicine needs an ecological theory of the body

2021· article· en· W3157466239 on OpenAlexaff
Joan E. M. Bratty

Bibliographic record

VenuecIRcle (University of British Columbia) · 2021
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBiomedicineEcologyGeographyBiology

Abstract

fetched live from OpenAlex

Family physicians were surveyed and interviewed during the COVID-19 pandemic to determine their perception of both pathogenic and symbiotic microbes. Evidence from a brief survey, a series of interviews and a review of recent literature suggests that a paradigm shift is occurring away from the germ theory of disease causation and towards an ecological theory of the human body. Conceptions of the human body are shifting from seeing the body as a nation-state at war with invading microbes towards an ecological view which sees human bodies as forming and embedded within microbial ecosystems, which are themselves under ecologic threat. The global challenge of antimicrobial resistance requires cross-disciplinary collaboration and a better understanding of how differing conceptions of the body and microbes may influence the success or failure of policies designed to minimize the inappropriate use of antimicrobial medications in clinical practice. Further research is needed to develop policies that encourage microbial stewardship as an alternative approach to antimicrobial stewardship.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.016
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0100.038
Scholarly communication0.0080.011
Open science0.0010.007
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0070.001

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 head0.012
GPT teacher head0.211
Teacher spread0.199 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreCommentary

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
Published2021
Admission routes1
Has abstractyes

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