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Record W2037791777 · doi:10.1016/j.pain.2007.04.041

The Pain Genes Database : An interactive web browser of pain-related transgenic knockout studies

2007· review· en· W2037791777 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePain · 2007
Typereview
Languageen
FieldNeuroscience
TopicPain Management and Placebo Effect
Canadian institutionsBlackberry (Canada)McGill University
Fundersnot available
KeywordsPhenotypeChronic painAllodyniaGeneStimulus (psychology)BioinformaticsMEDLINEKnockout mouseMedicineNociceptionHyperalgesiaBiologyComputational biologyDatabaseGeneticsNeurosciencePsychologyComputer science

Abstract

fetched live from OpenAlex

The transgenic knockout mouse is one of the most important tools of modern biology, and commonly employed by pain researchers to examine the function of genes of interest. Over 400 papers, at a current rate of >60 papers per year, have been published to date describing a statistically significant behavioral pain "phenotype" resulting from the null mutation of a single gene. The standard literature review format is incapable of providing a sufficiently broad and up-to-date overview of the field. We have therefore constructed the Pain Genes Database, an interactive, web-based data browser designed to allow easy access to and analysis of the published pain-related phenotypes of mutant mice (over 200 different mutants at the date of submission). Manuscripts describing results of pain-relevant knockout studies were identified via Medline search. Manuscripts were included in the database if they described the testing of a spontaneous or genetically engineered mutant mouse with null expression of a single gene on a behavioral assay of acute or tonic nociception, injury- or stimulus-induced hypersensitivity (i.e., allodynia or hyperalgesia), or drug- or stress-induced inhibition of nociception (i.e., analgesia), and reported at least one statistically significant difference between the mutant mice and their simultaneously tested wildtype controls. The database features two levels of exploration, one allowing the identification of genes by name, acronym, genomic position or "summary" phenotype, and the other allowing in-depth browsing, paper-by-paper, of specific phenotypes and test parameters. Links to genetic databases and Medline abstracts are provided for each gene and paper. It is our intention to update the database continually based on weekly Medline searches. This database should provide pain researchers with a useful and easy-to-use tool for the generation of novel hypotheses regarding the roles of genes and their protein products in pain processing and modulation. It can be accessed at http://paingeneticslab.ca/4105/06_02_pain_genetics_database.asp (or by visiting paingeneticslab.ca and clicking on the "Pain Genes Db" link under "Resources").

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)0.129
metaresearch head score (Gemma)0.033
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1290.033
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.154
GPT teacher head0.405
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