MétaCan
Menu
Back to cohort

Control of Breathing in Invertebrate Model Systems

2012· article· en· W4409117151 on OpenAlexaff
Harold J. Bell, Naweed I. Syed

Bibliographic record

VenueComprehensive physiology · 2012
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience of respiration and sleep
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsInvertebrateBreathingBiologyEcologyAnatomy

Abstract

fetched live from OpenAlex

Abstract The invertebrates have adopted a myriad of breathing strategies to facilitate the extraction of adequate quantities of oxygen from their surrounding environments. Their respiratory structures can take a wide variety of forms, including integumentary surfaces, lungs, gills, tracheal systems, and even parallel combinations of these same gas exchange structures. Like their vertebrate counterparts, the invertebrates have evolved elaborate control strategies to regulate their breathing activity. Our goal in this article is to present the reader with a description of what is known regarding the control of breathing in some of the specific invertebrate species that have been used as model systems to study different mechanistic aspects of the control of breathing. We will examine how several species have been used to study fundamental principles of respiratory rhythm generation, central and peripheral chemosensory modulation of breathing, and plasticity in the control of breathing. We will also present the reader with an overview of some of the behavioral and neuronal adaptability that has been extensively documented in these animals. By presenting explicit invertebrate species as model organisms, we will illustrate mechanistic principles that form the neuronal foundation of respiratory control, and moreover appear likely to be conserved across not only invertebrates, but vertebrate species as well. © 2012 American Physiological Society. Compr Physiol 2:1745‐1766, 2012.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.730
Threshold uncertainty score0.398

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 head0.070
GPT teacher head0.293
Teacher spread0.222 · 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 designBench or experimental
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

Citations0
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueComprehensive physiologySame topicNeuroscience of respiration and sleepFrench-language works237,207