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Record W2335425523 · doi:10.1097/scs.0b013e31826468de

Global Plastic Surgeons Images Depicted in Motion Pictures

2013· article· en· W2335425523 on OpenAlexaboutno aff
Se Jin Hwang, Sowhey Park, Kun Hwang

Bibliographic record

VenueJournal of Craniofacial Surgery · 2013
Typearticle
Languageen
FieldMedicine
TopicDigital Imaging in Medicine
Canadian institutionsnot available
FundersInha University
KeywordsMedicineMotion (physics)Point (geometry)Quarter (Canadian coin)Motion pictureSurgeryArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Motion pictures are made to entertain and enlighten people, but they are viewed differently by different people. What one considers to be a tearjerker may induce giggles in another. We have gained added interest in this because our professional pictures contain plastic surgery in their venue. We have recently reviewed 21 motion pictures that were made from 1928 to 2006 and that includes plastic surgical procedures in their content. As a habit, we tried to analyze them from a surgical point of view. About one third (35.7%) of the patients were criminals, whereas 14.3% of them were spies. One third of the procedures were done by illegitimate "surgeons," whereas a quarter of the procedures (25%) were performed by renowned surgeons. Surgeons who were in love with the patients did the rest (25%) of the operations. The complication rate was 14.3%; the surgery was successful in 85.7% of cases, but were the patients happy with the results? This was not the case in the movies. Only 7.7% were happy; 14.5 % of them were eminently unhappy. Why the discrepancy? It is difficult to analyze the minds of the people in the film, but considering that the majority of the characters in the films were rather unsavory, one may deduce that a crooked mind functions differently. Motion pictures have advanced greatly in the past several decades with the advent of improved mechanical and electronic devices, and plastic surgery as also advanced in tandem. This surgical field has become a common procedure in our daily life. It is readily available and mostly painless. However, the public sees it in only one way, that is, that the performing physicians are highly compensated. Very few consider the efforts and the suffering that accompanies each and every surgical procedure as it is performed. Perhaps, it is too much to hope for a day that will come when we will see a film that portrays the mental anguish that accompanies each and every procedure the plastic surgeon makes.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.085
Threshold uncertainty score0.284

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0850.013

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 head0.012
GPT teacher head0.263
Teacher spread0.251 · 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

Citations5
Published2013
Admission routes1
Has abstractyes

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