MétaCan
Menu
Back to cohort
Record W3083858412 · doi:10.3390/quat3030027

The LAST Coring Platform You Will Ever Need: Light, Affordable, Stable, and Transportable

2020· article· en· W3083858412 on OpenAlexaff
Olivier Blarquez, Julie C. Aleman

Bibliographic record

VenueQuaternary · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsCoringComputer scienceGeologyEngineeringMechanical engineeringDrilling

Abstract

fetched live from OpenAlex

Coring lakes and water bodies for paleoecological studies often involves using a coring platform to properly operate a sediment sampling device. In the past, coring platforms have been developed by specific paleoecology laboratories or by private companies. Those coring platforms are generally composed of two boats (inflatable boats, kayaks, etc.) connected together by a metallic and wood structure. While these coring platforms have proven their efficacy, they are not ideal in several coring settings requiring remote transportation, and their cost may be prohibitive for less funded paleoecological laboratories. On this technical note, we describe the Light, Affordable, Stable, and Transportable (LAST) coring platform. Coring platforms based on these principles and on the design presented herein have been extensively tested in various conditions and countries by our research group and collaborators. In the first part of this manuscript, we present the principles and the design of the LAST coring platform; then, we discuss the coring setting for which the LAST coring platform is suitable, and its possible limitations. Associated with this manuscript, we provide a construction and assemblage manual developed without words and with simple illustrations in order to make it easily accessible to speakers of any language.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.016
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.011

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 head0.023
GPT teacher head0.219
Teacher spread0.196 · 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 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

Citations1
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueQuaternarySame topicGeology and Paleoclimatology ResearchFrench-language works237,207