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Record W4310887003

Vegetable species consumed by Capromyspilorides Say in forests semideciduos of the peninsula of Guanahacabibes

2017· article· en· W4310887003 on OpenAlexaff
Fernando Ramón Hernández Martínez, Claudia Cruz Ramírez

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBanana Cultivation and Research
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsPeninsulaForestryGeographyEnvironmental scienceArchaeology
DOInot available

Abstract

fetched live from OpenAlex

The investigation was developed in the forest semideciduo of the peninsula of Guanahacabibes, in three different towns (Melones, Palma Sola andCabo Corrientes), having as objective: To determine the vegetable species used as feeding sources by the jutía conga and the consumed parts. For the obtaining of the data it was carried out the following methodology: In the same parcels where the count of groups fecal cool airs for the determination of the density was carried out, it was carried out a physical count of the plants that appeared consumed by the jutía, scoring, in each them, the parts that were used by this herbivore (bark, leaf, shaft, flowers and fruit). With the plants selectedas consumed by each town it was carried out an analysis of frequency, determining on this base the species more frequently used, as well as the parts of those that were used and their percent. They were determined a total of 34 species of plants of those which (23) are trees, (10) are bushes and (1) liana. The ones most frequently used are: Nectandracoriaceae; Schoepfiachrysophylloides; Drypeteslateriflora; Prunusmyrtifolius and Trophisracemosa. The parts with more percent of use were the leaves and the shaft with 15, 85%, continued by fruit and bark with 13, 91%.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.208
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0040.001
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 head0.305
GPT teacher head0.519
Teacher spread0.215 · 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 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
Published2017
Admission routes1
Has abstractyes

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