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Record W2551679361 · doi:10.3390/nu8110722

“English Disease”: Historical Notes on Rickets, the Bone–Lung Link and Child Neglect Issues

2016· review· en· W2551679361 on OpenAlexaff
Ming-Yong Zhang, Fan Shen, Anna Petryk, Jingfeng Tang, Xingzhen Chen, Consolato Sergi

Bibliographic record

VenueNutrients · 2016
Typereview
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsStollery Children's HospitalUniversity of Alberta HospitalAlberta Hospital EdmontonUniversity of Alberta
Fundersnot available
KeywordsRicketsNeglectMedicineLungLink (geometry)DiseasePathologyPediatricsInternal medicineVitamin D and neurologyPsychiatryComputer science

Abstract

fetched live from OpenAlex

Nutritional or classical rickets (here labeled as "rickets") is a worldwide disease involving mostly infants and young children having inadequate sunlight exposure, often associated with a low dietary intake of Vitamin D. Rickets targets all layers of society independently of economic status with historical information spanning more than two millennia. Vitamin D is critical for the absorption of calcium and prevention of rickets in children as well as osteomalacia in adults. The initial and misleading paradigm of the 19th and 20th centuries that rickets may have been the consequence of infection has been, indeed, reversed following the identification of the Vitamin D molecule's important role in the function of the immune system. Although traditionally considered limited to osteopathology, Vitamin D deficiency is now known to be linked to infection, inflammation, and carcinogenesis. In this review, we consider the key historical (Whistler, pre-Whistler and post-Whistler descriptors) and social facts around rickets; highlight the osteo-pathological features of rickets and the pathology of the upper and lower respiratory tract, stressing the fact that lungs remain the main secondary organ affected by Vitamin D deficiency; and emphasize the public health role in identifying the cases of child neglect or abuse based on the evaluation of the costochondral region.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.947
Threshold uncertainty score0.692

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.336
Teacher spread0.309 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations50
Published2016
Admission routes1
Has abstractyes

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