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10.1016/s1885-9070(08)35025-2

2000· book-chapter· en· W175837606 on OpenAlexvenueno aff
E. Michael Lewiecki

Bibliographic record

VenueTime to knit · 2000
Typebook-chapter
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

La osteoporosis es un trastorno esqueletico frecuente que se distingue por la reduccion de la resistencia osea y el aumento del riesgo de fractura. Las fracturas por fragilidad dan lugar a consecuencias clinicas graves, como dolor cronico, deformidades esqueleticas, perdida de la independencia y aumento de la tasa de mortalidad. A pesar de que el diagnostico y el tratamiento de la osteoporosis se consideran insuficientes, muchas pacientes tratadas toman la medicacion de forma incorrecta o no observan las pautas a lo largo de un periodo de duracion suficiente para beneficiarse de ellas. Entre las medidas encaminadas a evitar la osteoporosis cabe citar un estilo de vida sano, con ejercicio fisico regular, una ingesta adecuada de calcio y vitamina D, y la elusion del habito tabaquico y del consumo excesivo de alcohol. El diagnostico de las mujeres con riesgo de osteoporosis se realiza por medio de una sencilla prueba de densitometria osea con anterioridad a la aparicion de la primera fractura. El tratamiento farmacologico de aquellas mujeres con riesgo alto de fractura osteoporotica puede reducir la carga que suponen estas lesiones.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.012
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0050.005
Open science0.0040.005
Research integrity0.0080.003
Insufficient payload (model declined to judge)0.9880.991

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 head0.019
GPT teacher head0.250
Teacher spread0.231 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2000
Admission routes1
Has abstractyes

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