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Record W2336389922

Helpful when traditional therapies fail

2006· article· en· W2336389922 on OpenAlexaboutno aff
Jill Franklin

Bibliographic record

VenueEurope PMC (PubMed Central) · 2006
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAccident (philosophy)Psychology
DOInot available

Abstract

fetched live from OpenAlex

I thank Dr Lloyd-Smith for his thoughtful review of my book.1 Bringing the Auto Accident Survivor’s Guide for British Columbia to the attention of family physicians and recommending it for use with patients involved in motor vehicle accidents will help reduce the considerable anguish many patients have in dealing with the medical-legal-insurance system after an accident. My only quibble is with Dr Lloyd-Smith’s perception that alternative therapies are overemphasized in the book and traditional treatments understated. I’ve alluded to alternative therapies only briefly (once in a section on common rehabilitation and once in discussing late down-the-line treatment for those with spinal cord injury), noting that these treatments “can be helpful when traditional therapies fail to eliminate physical and psychological problems.” Traditional therapies are discussed more extensively, with physiotherapy noted to be the most frequently recommended treatment after motor vehicle accidents. Further mentions of alternative therapy refer solely to the difficulty of getting insurers to cover it, even when it is recommended by family physicians. I bring up this relatively minor point because of what I perceive to be an automatic rejection of alternative therapies by many physicians. Clearly, as I note in the Auto Accident Survivor’s Guide, these shouldn’t be the first approaches taken. They have, however, been helpful to many people who have already exhausted the remedies available through traditional channels and are still seeking relief. Whether these therapies work to the degree they do only because of the placebo effect is irrelevant to patients who are finally getting a measure of relief. I’m very grateful to my family physician in Vancouver, BC, for recommending alternative approaches to me when I was still in considerable pain many years after sustaining multiple fractures and soft tissue injuries when struck by a car while crossing the street. Some of her other patients had found relief through these treatments; I did as well. Dr Lloyd-Smith helpfully pointed out my erroneous mention of orthopedic surgeons as a resource in evaluating soft tissue injuries. This is, of course, the physiatrist’s role; this will be corrected in the next printing.

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)0.006
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.046
Threshold uncertainty score0.154

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0040.008
Scholarly communication0.0080.013
Open science0.0020.007
Research integrity0.0090.017
Insufficient payload (model declined to judge)0.0460.037

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 head0.065
GPT teacher head0.261
Teacher spread0.196 · 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 designNot applicable
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
Published2006
Admission routes1
Has abstractyes

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