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Record W2610564589 · doi:10.1201/9781315365671-17

Case Study: Medical Tourism—Recovery, Rainforests, and Restructuring: Opportunities for Hotels Bridging Healthcare (H2H)

2017· book-chapter· en· W2610564589 on OpenAlex
Frederick J. DeMicco

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueApple Academic Press eBooks · 2017
Typebook-chapter
Languageen
FieldHealth Professions
TopicGlobal Healthcare and Medical Tourism
Canadian institutionsnot available
Fundersnot available
KeywordsRestructuringBridging (networking)TourismBusinessHealth careRainforestMedical tourismGeographyComputer scienceEconomic growthEconomicsFinanceEcologyComputer securityBiology

Abstract

fetched live from OpenAlex

This chapter looks at medical tourism in Costa Rica. The role that a tropical rain forest plays in providing a natural and relaxed setting is explored. The relationship between a relaxed rain forest setting and other more main stream medical tourism settings and patient recovery is discussed. Fast-growing medical tourism in Costa Rica owes its existence to tourists from the United States and Canada traveling primarily to get medical and surgical procedures done abroad. Traditionally, the procedures that have been popular with medical tourists in Costa Rica have been cosmetic and dental treatments. But with growing standards of medical care, there is rapid medical tourism demand for various other surgeries and medical procedures. Many unique factors make Costa Rica healthcare a preferred medical travel destination. Medical treatments are usually about 50-70" cheaper than in the United States and no one has to wait their turn for surgery.

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.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.592
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0040.007
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 head0.282
GPT teacher head0.447
Teacher spread0.165 · 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