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Record W2462021299 · doi:10.1139/cjz-2015-0191

Differential growth of body segments explains ontogenetic shifts in organ position for the Diamondback Water Snake (<i>Nerodia rhombifer</i>)

2016· article· en· W2462021299 on OpenAlexvenueno aff
Gretchen E. Anderson, Stephen M. Secor

Bibliographic record

VenueCanadian Journal of Zoology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersDirectorate for Biological SciencesNational Science Foundation
KeywordsBiologyAnatomyVertebra

Abstract

fetched live from OpenAlex

As snakes grow, their organs move anteriorly relative to body size. We explored a developmental explanation for the ontogenetic shift in the relative position of internal organs for snakes using the Diamondback Water Snake (Nerodia rhombifer (Hallowell, 1852)). With age, this water snake’s heart, liver, small intestine, and right kidney move anteriorly by 2.5–5.0 percentage points of snout–vent length. The number of precaudal vertebrae did not vary due to size or sex. The anterior edge of the heart, liver, small intestine, and right kidney were typically aligned within a span of 4–8 vertebrae that likewise did not differ as a function of size or sex. Snakes exhibited a positive relationship between the number of precaudal vertebrae and the vertebra number aligned with each organ. Total length, centrum length, centrum width, ball width, height, and mass of eight vertebrae sampled at consistent vertebral number revealed that vertebrae in the middle region of the body grow at a greater rate than vertebrae at the anterior or distal ends of the body. For N. rhombifer, the observed forward shift in relative organ positions is the product of regional differences in the growth of body segments. Predictably, these differences arise from a developmental program generated by the differential expression of Hox genes.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.188
Teacher spread0.181 · 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 designObservational
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

Citations8
Published2016
Admission routes1
Has abstractyes

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