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Record W2022602119 · doi:10.1210/me.2015-1119

Editorial: What's in a Name, or the Impact of Misnomers in Endocrine Research

2015· editorial· en· W2022602119 on OpenAlexafffund
Vincent Giguère

Bibliographic record

VenueMolecular Endocrinology · 2015
Typeeditorial
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiomedical Text Mining and Ontologies
Canadian institutionsMcGill University
FundersMcGill University
KeywordsMisnomerObject (grammar)DiseaseMisattribution of memoryEpistemologyPsychologyBiologyMedicinePsychiatryComputer sciencePathologyCognitionPhilosophy

Abstract

fetched live from OpenAlex

The simplest definition of the word “misnomer” is that of a wrong name or inappropriate designation for a person, a place, or an object. Alternatively, in the case that interests us in this editorial, it can be a gene or its gene product. In everyday life, the use of misnomers, such as referring to a small meteorite entering the earth atmosphere as a “shooting star,” often has no practical consequence. In fact, misnomers such as this example can add a dose of poetry in our lives, allowing us to dream of distant universes for a brief moment. However, in medicine, the use of misnomers to identify a symptom or a disease can have more serious consequences, such as misdiagnosis or incorrect treatments, even by welltrained physicians. A quick search of PubMed yields a long list of such occurrences that includes, for example, the misnomer “lupus anticoagulant,” a coagulation inhibitor originally identified in patients with systemic lupus erythematosus, but its presence is actually associated with thromboembolic events that may strike in otherwise healthy individuals (1). In medical research, the consequences of using misnomers might be less dire but, nonetheless, can lead some misguided investigators to pursue research projects in the wrong direction, misinterpret the results of their investigations, alter the conclusion of their work, and at worst, perpetuate false concepts and deceptive hypotheses. Although the routine use of misnomers is more often an annoyance than a critical threat to medical research, this phenomenon can stunt progress and further demonstrates a certain lack of rigor in the scientific process. In the biological sciences, misnomers can originate from the fact that a gene/protein has two or more possible functions, but that the name in use reflects a minor or even a physiologically irrelevant function of the gene/protein rather than its true role(s). Misnomers also arise because the entity named received its designation based on the first alleged function assigned to it, long before its true function was recognized. A paradigm for these occurrences is the superfamily of nuclear receptors, in which misnomers are widespread. The problems for this group of genes are further compounded in that many nuclear receptors were codiscovered by different groups, each using a different name for the same receptor. In 1999, researchers in the field agreed to a new nomenclature to unambiguously identify each nuclear receptor (2). The nomenclature was based on subfamilies and groups of receptors as part of a phylogenetic tree that connects all known nuclear receptor sequences, and each receptor was assigned an alphanumeric name analogous to a “postal code.” It was recommended that the receptor(s) be identified by the official name(s) at least once in a manuscript, preferably in the abstract and/or the introduction. Once the receptor was matched to its “official name or code,” authors were then encouraged to use the trivial name for the remainder of the manuscript. More on that subject later. Although the use of this nomenclature restored some order in this dysfunctional family, not all authors com-

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 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)0.001
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.007
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
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 head0.039
GPT teacher head0.410
Teacher spread0.370 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEditorial

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

Citations2
Published2015
Admission routes2
Has abstractyes

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