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Record W2148132100 · doi:10.2174/138161209788186263

Acid Sensing Ion Channels and Acid Nociception

2009· review· en· W2148132100 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

VenueCurrent Pharmaceutical Design · 2009
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon Transport and Channel Regulation
Canadian institutionsCelluForce (Canada)
Fundersnot available
KeywordsAcid-sensing ion channelNociceptionIon channelNeuroscienceSensory systemNociceptorMedicineChemistryBiologyInternal medicineReceptor

Abstract

fetched live from OpenAlex

Acid Sensing Ion Channels (ASICs) are a family of cation channels expressed principally in neurons and that are activated by protons. The sensitivity of ASICs to acidosis and their distribution in primary sensory neurons points to a significant role of these channels in acid nociception. However, despite the fact that the first ASIC was identified more than 10 years ago the physiological and pathophysiological role of this channel family remains poorly understood. In this paper, the available body of data (genetic, pharmacological, and other) on ASICs will be reviewed and the role of ASIC in normal nociception and other pain sensations will be discussed. Some of the recent drug discovery and development activities ongoing in our laboratory, which point to ASICs being a relevant target for pain modulation, will also be summarized.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.140
GPT teacher head0.398
Teacher spread0.258 · 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