MétaCan
Menu
Back to cohort
Record W7144100501 · doi:10.15017/6796276

木柵護岸を伴う農業水路の多面的機能:淡水魚の保全効果の評価および炭素貯蔵量の試算

2023· article· ja· W7144100501 on OpenAlexaff
Norio Onikura, Miki Ichiyasu

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2023
Typearticle
Languageja
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsNutrasource
Fundersnot available
KeywordsRevetmentSpecies richnessThreatened speciesFaunaDitchBiodiversityIrrigation district

Abstract

fetched live from OpenAlex

Freshwater fish fauna was compared among 5 types of revetments: wooden revetment, block mat revetment, and other three types by Onikura et al.(2007) in irrigation canals and ditches in the Chikugo and Saga Plains. The block mat revetment had negative effect on fish species richness and appearances of several threatened species, while the wooden revetment was evaluated to have a high conservation effect on the species richness because the average number of species were almost as same as the earth revetment. However, wooden revetment was shown to be impact on only golden venus chub among the threatened species. Therefore, in the future management and reconstruction of wooden revetments, it is necessary to consider the environmental preference of this fish. From the wood consumption of the wooden revetment in irrigation canals and ditches reconstructed by Saga Prefecture since 2012, the carbon storage quantity was estimated to exceed 40,000 ton-CO^2, which was estimated to be equivalent to about 15,000 times of annual CO^2 emission per household. These results support that the canals and ditches of the wooden revetment has not only previous multifaceted function but also a biodiversity conservation and a carbon storage function.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.250
Teacher spread0.232 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueInstitutional Repositories DataBase (IRDB)Same topicFish Ecology and Management StudiesFrench-language works237,207