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Record W2337961971

Uji banding empat bahan pengencer untuk preservasi semen anjing retriever

2008· article· id· W2337961971 on OpenAlexaboutno aff
A. Wicaksono, Raden Iis Arifiantini

Bibliographic record

Venuenot available
Typearticle
Languageid
FieldMedicine
TopicSperm and Testicular Function
Canadian institutionsnot available
Fundersnot available
KeywordsDiluentSemenSpermAndrologyExtenderLabrador RetrieverSperm motilityChemistryAnimal scienceBiologyMedicineSurgery
DOInot available

Abstract

fetched live from OpenAlex

WICAKSONO, A. and R.I. ARIFIANTINI. 2009. Comparison of four diluents for the retriever dogs semen preservation. JITV 14(1): 50-57. The quality of chilled semen depends on the composition of diluent. The choice of the buffer, anti-cold shock and nutrition sources can be the first decision in order to choose appropriate diluents. Nowadays a lot of diluent are used for canine semen preservation such as Tris buffer and Citrate buffer. This study was aimed to observe the differences of diluent for preserving Retriever dog spermatozoa. The semen sample collected from four Retriever dogs with three times repetition. The semen was evaluated macro-and microscopically. The semen with >70% sperm motility was divided into four tubes and diluted with diluter 1 (P1), diluter: P2, P3 and P4 (modified P3). The diluted semen was divided into two tubes and each sample was stored at room and 5 0 C temperature. The viability of chilled semen was observed every 3 hours at room temperature and 12 hours at 5 0 C. The result showed that P2 keep the sperm viability better than the other diluents. On 5 0 C at 24 hours storage P2 showed the highest motile and live sperm percentage (46.25 ± 0.22%; 57.11 ± 0.25%). In room temperature at 6 hours P2 showed the highest motile and live sperm percentage (40.94 ± 0.20%; 52.65 ± 0.23%). It is concluded that P2 can keep the sperm viability by 84 hours of 5 0 C and 21 hours at room temperature.

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)0.000
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: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.002

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 head0.050
GPT teacher head0.267
Teacher spread0.218 · 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

Citations5
Published2008
Admission routes1
Has abstractyes

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