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The clinician's response to common physical complaints

2004· book-chapter· en· W426174330 on OpenAlexaff
C. Laird Birmingham, P. J. V. Beumont

Bibliographic record

VenueCambridge University Press eBooks · 2004
Typebook-chapter
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsVomitingMedicineTable (database)Physical examPhysical examinationPsychologyPhysical therapySurgeryComputer scienceData mining

Abstract

fetched live from OpenAlex

Many of the physical symptoms of AN arerelated directly to the effects of semi-starvation, while other physical symptoms areassociated mainly with behavioral problems such as excessive exercising, vomiting, and purging. Table 5.1 lists the most common physical manifestations in AN. Table 5.2 lists the physical manifestations most commonly found in BN. Edema Case A 25-year-old female gains 10 kg in seven days. She is extremely anxious and agitated and threatens to discharge herself against medical advice. The nurse asks you why she has gained so much weight. Comment During feeding, edema occurs due to volume depletion, low metabolic rate, behaviors such as vomiting and laxative, enema, and diuretic use, which cause the body to have high circulating hormones that promote the retention of fluid. Antidiuretic hormone is secreted by the pituitary, renin is secreted by the kidney, angiotension is formed in the blood, and aldosterone is produced by the adrenal gland. The amount of fluid that might be retained in a patient is impossible to predict, but it is often 3—5 kg of water. The fluid retention is much greater in patients with a history of binge—purge behavior or diuretic use. If the patient is suspected of having edema, apply steady, firm pressure with the pad of your thumb over the skin covering the lower tibia, just about the ankle. After 15 seconds, a small pit will appear if edema is present.

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)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.038
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0380.010

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 head0.035
GPT teacher head0.290
Teacher spread0.255 · 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 designObservational
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

Citations0
Published2004
Admission routes1
Has abstractyes

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