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Record W2159679944 · doi:10.1017/s0952836901000796

Observations on the diet and habitat of the mountain tapir (<i>Tapirus pinchaque</i>)

2001· article· en· W2159679944 on OpenAlexaff
Craig C. Downer

Bibliographic record

VenueJournal of Zoology · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversity College of the North
Fundersnot available
KeywordsHabitatEcologyBiologySeed dispersalChaparralGrasslandNational parkAbundance (ecology)ShrublandGeographyBiological dispersal

Abstract

fetched live from OpenAlex

Abstract Results of a 4‐year study in Sangay National Park, Ecuador, indicated that the mountain tapir Tapirus pinchaque , consumes a wide variety of woody and non‐woody plant taxa primarily as a foliose browser, and has a preference for some nitrogen‐fixing plants. The more closed‐cover Andean forest and chaparral habitats contain a greater abundance of mountain tapir‐favoured food than the more open grassland paramo, riverine meadow, and pampas vegetation types. Andean forests are considered the most critical habitat for the survival of this tapir because of their provision of cover and food. Field observations and results of faecal germination experiments show that the mountain tapir assists in the successful seed dispersal of many species of Andean plants. Significant regressions between: (1) seed germination and (2) both the natural logarithm (ln e ) of the preference ratio and the dietary abundance of food species indicate a mutualism between the mid to high montane‐dwelling mountain tapir and the plants it consumes. A significant relation during the past 2 to 3 million years is proposed between: (1) the crossing of the Panamanian Isthmus and the occupation of the mid to high northern Andes by ancestors of the mountain tapir, and (2) the rise of the Andes and formation of the montane forest and paramo ecosystems above c. 2000 m elevation.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

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)0.0020.000

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 head0.020
GPT teacher head0.220
Teacher spread0.200 · 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

Citations62
Published2001
Admission routes1
Has abstractyes

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