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Record W1999908233 · doi:10.1373/clinchem.2009.127092

Unveiling the Right Side: How to Win Wimbledon Championships: Creating Beklof and Vamos

2009· article· en· W1999908233 on OpenAlexaff
Eleftherios P. Diamandis

Bibliographic record

VenueClinical Chemistry · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsMount Sinai Hospital
Fundersnot available
KeywordsWifeHobbyBedroomTechnicianGirlPsychologyVisual artsHistoryLawArtPolitical science

Abstract

fetched live from OpenAlex

I am a 60-year old tennis fanatic. I’ve built tennis courts on 2 of my properties and as a hobby, I search for old, wooden tennis racquets at garage sales—I possess more than 200 of them already! I have 2 children, a girl and a boy (both in their early 30s), and I always dreamed they would become tennis champions. They started playing at the age of 4, and I did everything I could to promote them in the sport. Unfortunately, neither of them made it to the ranks. My daughter did not play enough, and my son, who has a fierce forehand, injured his shoulder and can no longer serve. We now just play on weekends, and I am a bit disappointed that my aspirations for them winning Wimbledon Championships were never fulfilled. I do not believe I am alone in this situation. I am certain that after watching the Beijing Olympics, many of us would have been proud to be the parents of such phenoms as Michael Phelps or Usain Bolt. Recently, however, science has given us hope that it may not be too late for us to fulfill or surpass some of our unmet dreams. For example, with new technology, I could become a father even at the age of 100! My wife could achieve the same goal. Here is how it will be done: somebody will pick up a few cells from my own and my wife’s skin using adhesive tape. A technician will then insert 4 genes (maybe fewer in the future; this can be done within a couple of days) to reprogram these cells to become pluripotent stem cells (1). Then, using some magic additives, these pluripotent stem cells could differentiate into germ cells, which could then be combined to form human embryos. I’ve been advised by a company providing this service (Children by the Dozen®) that I can create as many embryos as I like. For every 11 children I contract them to do, the 12th is free! Another big thing that is coming about is the artificial placenta (2). Embryos can be implanted in a plastic bag–like device and connected to this placenta, and from there to a machine that will pump nutrients while the embryos float. When the embryos mature, you can pick them up from the tank and take them home with the same ease as you do with a live lobster or rainbow trout. These improvements alone could not solve the problem of producing tennis champions without the invention of “genomewide scans,” which identify where in the genome the talent of each person lies. For example, with current technology, in a matter of days one can combine the talents of Federer and Nadal, or the talent and beauty of Maria Sharapova, with genetic elements like single nucleotide polymorphisms. These talent-related DNA segments can then be manufactured into “genetic cassettes,” which can be inserted at the embryonic stage, to give the fetus any superpower you want. Genetic cassettes could be available in supermarket freezers, alongside your favorite ice creams. The package would have the picture of your favorite superstar on the outside: Usain Bolt, Michael Phelps, Roger Federer, David Beckham, Albert Einstein, Brad Pitt, Larry King, John Lennon, Barack Obama, or even George W. Bush (!?). For women, bestsellers could include: Oprah Winfrey, Paris Hilton, Maria Sharapova, Venus Williams, Angelina Jolie, Hillary Clinton, Shania Twain, Mother Theresa, Queen Elizabeth, or Madonna. Now, I believe, I have a solution to my problem. Using new technologies, I could produce a few embryos in which I could insert certain cassettes at the embryonic stage. For example, my son Beklof could be created with “cassettes” from Beckham, Einstein, King, Lennon, Obama, and Federer. My daughter Vamos could be created from Venus, Angelina, Maria, Oprah, and Shania. There is no question that my “technological kids” should not be smart, athletic, artistic, good-looking, rock-stars, good liars (pardon; politicians) and, at the same time, very rich! I am now a 78-year-old father of two 18-year old “technological kids,” Beklof and Vamos. I also have 4 lovely grandchildren, 2 from each of my “natural” children. They are about the same age as my “t-kids”. Looking back, I have some regrets about the decision to have my t-kids at an older age. Taking care of them was difficult considering my arthritis, high-blood pressure, early Alzheimer, cataract, benign prostatic hyperplasia, diabetes and chronic fatigue syndrome. I much prefer the duties of a granddad, playing with my grandchildren at will and then passing them back to their parents. Anyway, it is too late now. When Beklof was 13, I took him to the local soccer club for a trial. The coach told me that he is a good player but he could not “bend it like Beckham”. I was surprised and went back to “Children by the Dozen” to complain. They said they would do some DNA testing and get back to me. When they did, they said that one SNP from Beckham’s genetic cassette was responsible for “bending it”, and was inadvertently omitted. It was a tough pill to swallow. When Beklof was 14, I noticed that his math marks were not 100%! When I inquired about it, they told me that Einstein’s DNA was slightly old when it was recovered from his tomb and the sequencing was ambiguous in several spots. I was still hopeful that Beklof could become the “King of TV talk shows”, since he was carrying the Larry King genetic cassette. While genetic testing showed no mistakes in the cassette, the company told me they had discovered an unusual somatic translocation which silenced the cassette entirely. Further investigations revealed that Lennon’s cassette failed to incorporate, likely due to his excessive use of marijuana. When we came to Obama, the company admitted that during the incubation process at the embryonic stage, an unexpected electrical surge shut down the machine, cutting nutrients to the embryo for a few minutes and preventing future expression of this cassette. I still had hopes that Beklof would win a few Wimbledons, since his Federer cassette was fully operational. I was so happy when Beklof competed in a city-wide junior championship, playing well and reaching the finals. I was telling myself that this is it. I was shocked when Beklof lost in the finals with a score of 6–0, 6–0, 6–0 to a guy by the name of Blanfar. This other guy was truly amazing. I had never seen anyone play tennis like him and I was anxious to find out more; no surprise, he was another “t-kid”. In doing more research, I found out that his father was not as greedy as me and had concentrated on creating a tennis player and not a multitalented son. I hired a private detective who found out that Blanfar carried the cassettes for Borg, Laver, Agassi, Nadal, Federer, Ashe, and Roddick. Well, at least I still had Vamos to count on. But she never displayed the signature lips of Angelina. On reading the National Enquirer, I found out that Angelina’s lips have nothing to do with genetics, but instead, with injections of Botox®. I was in shock when I found out that Vamos could not even hit a tennis ball. The company told me that it was a fatal mistake to mix genetic cassettes from an American (Williams) and a Russian (Sharapova). I had inadvertently started a “cold war” within Vamos’ body! And what about the Oprah cassette? Well, at the time of cloning, they didn’t know that in the “talent-containing region”, there is a locus encoding for a micro-RNA that shuts down 1 MB of surrounding sequence. Poor Vamos … I still hoped that she could sing; and she did as well as Shania, until she was 12. Then, she contracted mononucleosis and the Epstein-Barr virus was incorporated into her DNA, within the Shania cassette. After that, her voice was no better than Bob Dylan’s. Author Contributions:All authors confirmed they have contributed to the intellectual content of this paper and have met the following 3 requirements: (a) significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; (b) drafting or revising the article for intellectual content; and (c) final approval of the published article. Authors’ Disclosures of Potential Conflicts of Interest:No authors declared any potential conflicts of interest. Role of Sponsor: The funding organizations played no role in the design of study, choice of enrolled patients, review and interpretation of data, or preparation or approval of manuscript.

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)0.002
metaresearch head score (Gemma)0.005
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: Other · Consensus signal: Other
Teacher disagreement score0.037
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.000
Science and technology studies0.0100.004
Scholarly communication0.0090.009
Open science0.0020.009
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0370.013

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 head0.034
GPT teacher head0.347
Teacher spread0.312 · 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
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".

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Citations1
Published2009
Admission routes1
Has abstractyes

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