Evidence map›Paper›PMID 41627611›Full record

ArticleTropical animal health and production2026

Reply to the comment on: comparison of machine learning algorithms and multiple linear regression for live weight estimation of Akkaraman lambs.

Özge Kozaklı, Ayhan Ceyhan, Mevlüt Noyan

Abstract readLetter
PubMed Publisher
In one paragraph

Article in Tropical animal health and production, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Özge KozaklıDepartment of Animal Production and Technologies, Faculty of Agricultural Sciences and Technologies, Niğde Ömer Halisdemir University, Niğde, 51240, Türkiye. ozgekozakli94@hotmail.com.ORCID http://orcid.org/0000-0003-4201-1157
Ayhan CeyhanDepartment of Animal Production and Technologies, Faculty of Agricultural Sciences and Technologies, Niğde Ömer Halisdemir University, Niğde, 51240, Türkiye.ORCID http://orcid.org/0000-0003-2862-7369
Mevlüt NoyanNiğde Ömer Halisdemir University, Bor Vocational School, Bor/Niğde, 51700, Türkiye.ORCID http://orcid.org/0000-0001-6777-5861

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The authors appreciate the insightful interest and constructive remarks made by Hinpetch Daungsupawong and Viroj Wiwanitkit (2024) in their correspondence entitled “A comment on Comparison of machine learning algorithms and multiple linear regression for live weight estimation of Akkaraman lambs,” recently published in Tropical Animal Health and Production (Vol. 56, Article 338). This reply aims to clarify certain methodological aspects of our study that may have been misunderstood and to further elaborate on the analytical procedures employed in our research for the sake of transparency and scientific accuracy. The authors hope that this clarification will be useful for readers and researchers working on similar predictive modeling studies in livestock science.

Indexed as

Body WeightMachine LearningSheep, DomesticAnimalsLinear ModelsPrediction AlgorithmsPredictive Learning ModelsSheepAkkaraman lambsCorrespondenceFeature selectionLivestock scienceLive weight predictionMachine learningModel comparisonMulticollinearityMultiple linear regressionPredictive modeling

Identifiers

PMID41627611

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.