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Record W2972016865 · doi:10.5539/sar.v8n4p28

Longevity of Nelore Cows of the Bolivian Tropics. Is It Possible to Explain It Through Productive Variables?

2019· article· en· W2972016865 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSustainable Agriculture Research · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainable Agricultural Systems Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsLongevityBreedIce calvingTropicsAnimal scienceMulticollinearityZebuBiologyWeaningProductivityMathematicsLactationStatisticsPregnancyEcologyRegression analysis

Abstract

fetched live from OpenAlex

The objective of this work was to evaluate the longevity and its relationship with productive variables of Nelore cows in grazing systems of the Bolivian tropics. Retrospective data were used corresponding to 259 Nelore breed cows, primiparous and multiparous discarded with a total of 800 births, in the period between 2005 and 2019, belonging to the Cooperativa Agropecuaria Integral San Juan de Yapacaní (CAISY) located in the San Juan Japanese Communities, Santa Cruz, Bolivia. The variables analyzed were: Live weight of cow (WC) in kg, Weight of the calf at birth (WCB) in kg, Weight of calf at weaning (WCW) in kg, Total weight of weaned calf (WWC) in kg, Age at first calving (AFC) in months, Number of calvings (NC), Longevity (L) in days, Calf Index (CI) in kg, Accumulated Productivity (PAC) in kg, Total calf production (CP) in kg, Efficiency of Stock (ES) in kg. In order to respond to the main objective of this work, the relationship between the life longevity of the cow and the other productive variables was studied. For this, first principal component analysis (PCA) was carried out, by means of which the space dimension of the productive variables was reduced creating new linearly independent variables and in this way avoid problems of multicollinearity in the model, because the productive variables in some cases turned out to be correlated. Then, the first three main components that explain 77% of the total variability of the data were retained and interpreted as follows: The PC1 was high and directly correlated with the variables NC, Kg produced total, % of stock efficiency, PAC and Kg produced meat / day, therefore can be thought of as an indicator of "productive efficiency". PC2 was an indicator of "efficiency in rebreeding" since it presented altar and direct correlations with WC and AFC. PC3 was high and directly correlated with birth weight and weaning weight, which is interpreted as an indicator of "breeding efficiency". Finally, a multiple linear regression model was adjusted considering Longevity as a function of productive efficiency, breeding efficiency and rebreeding efficiency (p-value <0.0001 in the three cases). 87% of the total variability of L (days) is explained by the model. It is concluded that Longevity is related to productive indicators for this group of Nelore cows in grazing systems of the Bolivian tropics.

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.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.365
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.007
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.002
Research integrity0.0000.001
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 head0.021
GPT teacher head0.298
Teacher spread0.276 · 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