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Record W4295419575 · doi:10.1038/s41598-022-17679-x

Collecting critically endangered cliff plants using a drone-based sampling manipulator

2022· article· en· W4295419575 on OpenAlexafffund
Hughes La Vigne, Guillaume Charron, Julien Rachiele-Tremblay, David Rancourt, Ben Nyberg, Alexis Lussier Desbiens

Bibliographic record

VenueScientific Reports · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife-Road Interactions and Conservation
Canadian institutionsInstitut interdisciplinaire d'innovation technologiqueUniversité de Sherbrooke
FundersMitacsStrongMohamed bin Zayed Species Conservation FundNatural Sciences and Engineering Research Council of CanadaUniversité de SherbrookeNational Geographic Society
KeywordsDroneCritically endangeredCliffEndangered speciesSampling (signal processing)Computer scienceBiologyGeographyEcologyHabitatComputer visionArchaeologyBotany

Abstract

fetched live from OpenAlex

Kaua'i, an island within the Hawai'i archipelago, is home of a unique flora that contains 250 single-island endemic plant species. Threats have led to a significant population decrease where 97% of these plant species are now listed as endangered, critically endangered, or extinct. Vertical cliff habitats on Kaua'i work as refugia to protect plants from their stressors. However, this habitat makes conservation work particularly difficult, forcing scientists, and botanists to use risky and time-consuming methods such as abseiling to access remote plant populations. Here we present the Mamba, the first aerial system capable of sampling plants on cliffs. This system is operated by two pilots and consists of an actively controlled platform suspended by a long cable under a lifting drone. Eleven otherwise inaccessible samples from five critically endangered species were collected during the first field trials on Kaua'i Island. The samples are currently surviving in nurseries, demonstrating that the Mamba can be used to complete the conservation life cycle for organisms located in difficult areas, from location to collection, then cultivation and outplanting.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
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 score0.482
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.057
GPT teacher head0.292
Teacher spread0.236 · 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.

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

Citations31
Published2022
Admission routes2
Has abstractyes

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