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Record W1036910567 · doi:10.1017/cbo9780511489150.007

The segmented phenotype

2006· book-chapter· en· W1036910567 on OpenAlexaboutno aff
Andrew Lakoff

Bibliographic record

VenueCambridge University Press eBooks · 2006
Typebook-chapter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsPhenotypeComputational biologyBiologyGeneticsGene

Abstract

fetched live from OpenAlex

In April 2003, the United States Patent and Trade Office awarded a patent to Genset for its invention of a gene associated with psychiatric illness. “The invention,” read the patent, “provides means to identify compounds useful in the treatment of schizophrenia, bipolar disorder, and related diseases, means to determine the predisposition of individuals to said disease, as well as means for the disease diagnosis and prognosis.” The patented gene, on the long arm of chromosome 13, had been identified using DNA extracted from schizophrenia patients in a Quebecois population as part of a collaboration between Genset and Janssen Pharmaceuticals. In the short term the implications of the patent, and related findings published in scientific journals, were unclear. For one thing, the same genetic variant had also been found among Genset's Argentine bipolar samples. Thus, rather than stabilizing the diagnostic entities – schizophrenia and bipolar disorder – that had been used in the company's search for genes linked to susceptibility to mental illness, the finding seemed to undermine them. Moreover, the basic unit of information that was the object of the patent was elusive: the list of possible entities ranged from “gene,” to “biallelic marker,” to “susceptibility locus,” to an “isolated nucleic acid” comprising the “open reading frame” that encoded the gene's protein product. Indeed, the meaning or usefulness of the word “gene” was no longer certain in the field of molecular biology: the postwar paradigm of the genetic code or blueprint was in question in the wake of the completion of the Human Genome Project.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.071
Threshold uncertainty score0.238

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0710.012

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 head0.198
Teacher spread0.186 · 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 designTheoretical or conceptual
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

Explore more

Same venueCambridge University Press eBooks→Same topicGenetic Associations and Epidemiology→French-language works237,207→