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Record W2027734344 · doi:10.1139/z03-007

Venom injection by rattlesnakes (<i>Crotalus atrox</i>): peripheral resistance and the pressure-balance hypothesis

2003· article· en· W2027734344 on OpenAlexvenueno aff
Bruce A. Young, Molly Phelan, Malinda Morain, Melissa Ommundsen, Robert A. Kurt

Bibliographic record

VenueCanadian Journal of Zoology · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVenomous Animal Envenomation and Studies
Canadian institutionsnot available
Fundersnot available
KeywordsVenomBiologyFangPeripheralCrotalusAnatomyZoologyMedicineInternal medicineEcology

Abstract

fetched live from OpenAlex

Differential venom injection by snakes, between two size classes of prey for example, has typically been explained within the rubric of the venom-metering hypothesis, which claims that snakes decide how much venom to inject in a given strike. Recently, an alternative, the pressure-balance hypothesis, was advanced, which attributes differential venom flow to the balance of internal forces acting at the venom gland and venom chambers and external forces acting at the exit orifice of the fang. This study tests these competing hypotheses. High-speed digital videos of predatory and defensive strikes by western diamondback rattlesnakes, Crotalus atrox, revealed considerable variation in the trajectory of the fang relative to the target, which would yield wounds with potentially different levels of peripheral resistance. The importance of peripheral resistance was also suggested by the expulsion of venom from the fang after withdrawal from the target (in 7% of strikes) and by the forceful ejection of fluid from the target around the embedded fang (in 2.8% of strikes). Experimental milking chambers were constructed that exposed the right and left venom-delivery systems to different levels of peripheral resistance; with increased peripheral resistance significantly less venom was injected into the chamber and significantly more venom was released on the chamber's surface.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.489
Threshold uncertainty score0.556

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.005
GPT teacher head0.184
Teacher spread0.179 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations15
Published2003
Admission routes1
Has abstractyes

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