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Record W2965660131 · doi:10.35513/21658005.2019.1.9

Insectivory characteristics of the Japanese marten (Martes melampus): a qualitative review

2019· review· en· W2965660131 on OpenAlexaff
Masumi Hisano

Bibliographic record

VenueZoology and Ecology · 2019
Typereview
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsLakehead University
Fundersnot available
KeywordsMartenBiologyPredationArboreal locomotionEcologyZoologyGeneralist and specialist speciesNest (protein structural motif)Habitat

Abstract

fetched live from OpenAlex

Insects are rich in protein and thus are important substitute foods for many species of generalist feeders. This study reviews insectivory characteristics of the Japanese marten (Martes melampus) based on current literature. Across the 16 locations (14 studies) in the Japanese archipelago, a total of 80 different insects (including those only identified at genus, family, or order level) were listed as marten food, 26 of which were identified at the species level. The consumed insects were categorised by their locomotion types, and the Japanese martens exploited not only grounddwelling species, but also arboreal, flying, and underground-dwelling insects, taking advantage of their arboreality and ability of agile pursuit predation. Notably, immobile insects such as egg mass of Mantodea spp, as well as pupa/larvae of Vespula flaviceps and Polistes spp. from wasp nests were consumed by the Japanese marten in multiple study areas. This review shows dietary generalism (specifically ‘food exploitation generalism’) of the Japanese marten in terms of non-nutritive properties (i.e., locomotion ability of prey).

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.049
GPT teacher head0.344
Teacher spread0.295 · 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 designQualitative
Domainnot available
GenreReview

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

Citations4
Published2019
Admission routes1
Has abstractyes

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