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Record W2231846022 · doi:10.1242/bio.012922

Direct lateral maneuvers in hawkmoths

2016· article· en· W2231846022 on OpenAlexfundno aff
Jeremy S. M. Greeter, Tyson L. Hedrick

Bibliographic record

VenueBiology Open · 2016
Typearticle
Languageen
FieldEngineering
TopicBiomimetic flight and propulsion mechanisms
Canadian institutionsnot available
FundersUniversity of British Columbia
KeywordsBiologyComputational biologyBioinformatics

Abstract

fetched live from OpenAlex

We used videography to investigate direct lateral maneuvers, i.e. 'sideslips', of the hawkmoth Manduca sexta. M. sexta sideslip by rolling their entire body and wings to reorient their net force vector. During sideslip they increase net aerodynamic force by flapping with greater amplitude, (in both wing elevation and sweep), allowing them to continue to support body weight while rolled. To execute the roll maneuver we observed in sideslips, they use an asymmetric wing stroke; increasing the pitch of the roll-contralateral wing pair, while decreasing that of the roll-ipsilateral pair. They also increase the wing sweep amplitude of, and decrease the elevation amplitude of, the contralateral wing pair relative to the ipsilateral pair. The roll maneuver unfolds in a stairstep manner, with orientation changing more during downstroke than upstroke. This is due to smaller upstroke wing pitch angle asymmetries as well as increased upstroke flapping counter-torque from left-right differences in global reference frame wing velocity about the moth's roll axis. Rolls are also opposed by stabilizing aerodynamic moments from lateral motion, such that rightward roll velocity will be opposed by rightward motion. Computational modeling using blade-element approaches confirm the plausibility of a causal linkage between the previously mentioned wing kinematics and roll/sideslip. Model results also predict high degrees of axial and lateral damping. On the time scale of whole and half wing strokes, left-right wing pair asymmetries directly relate to the first, but not second, derivative of roll. Collectively, these results strongly support a roll-based sideslip with a high degree of roll damping in M. sexta.

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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.018
GPT teacher head0.247
Teacher spread0.229 · 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

Citations24
Published2016
Admission routes1
Has abstractyes

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