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Record W2606014919 · doi:10.2527/tas2017-0016

Analysis of lactation feed intakes for sows with extended lactation lengths

2017· article· en· W2606014919 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueTranslational Animal Science · 2017
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLactationParity (physics)Akaike information criterionAnimal scienceMathematicsStatisticsBiologyPregnancyPhysics

Abstract

fetched live from OpenAlex

Abstract The objectives of this research were to quantify and model daily feed intakes to 28 d of lactation in modern sows. A total of 4,512 daily feed intake (DFI) records were collected for 156 Hypor sows from February 2015 to March 2016. The mean lactation length was 27.9 ± 2.0 d. The data included 9 parity 1, 33 parity 2 and 114 parity 3+ sows. Data were collected using a computerized feeding system (Gestal Solo, JYGA Technologies, Quebec, Canada). The feeding system was used to set an upper limit to DFI for the first 7 d of lactation. Overall, the least-squares means of a model including the random effect of sow indicated that DFI's continued to slowly increase to 28 d of lactation. The DFI data were fitted to Generalized Michaelis-Menten (GMM) and polynomial functions of day of lactation (t). The GMM function [DFIi,t (kg/d) = DFI0 + (DFIA − DFI0)(t/K)C/[1 + (t/K)C]] was fitted with 2 random effects for DFI (dfiAi) and intercept (dfi0i) using the NLMIXED procedure in SAS®. The polynomial function DFIi,t (kg/d) = [B0 + B1 t + B2 t2 + B3 t3 + B4 t4] was fitted with three random effects for B0, B1, and B2 using the MIXED procedure in SAS®. Fixed effects models of the two functions had similar Akaike's Information Criteria (AIC) values and mean predicted DFI's. The polynomial function with 3 random effects provided a better fit to the data based on R2 30 (0.81 versus 0.79), AIC (14,709 versus 15,158) and RSD (1.204 versus 1.321) values than the GMM function with two random effects. The random effect for B2 in the polynomial function allowed for the fitting of the function to lactation records that had decreased DFI after 15 d of lactation. The random effects for the polynomial function were used to sort the lactation records into three groups based on the derivative of the function at 21 d of lactation. Lactation records of the three groups had similar DFI the first two weeks of lactation (P > 0.40). The three groups of sows had substantially different DFI's after 18 d of lactation (P < 0.028). The differences in both actual and predicted DFI's between the three groups increased with each day of lactation to day 28 (P < 0.001). Mixed model polynomial functions can be used to identify sows with different patterns of DFI after 15 d of lactation.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.625
Threshold uncertainty score0.640

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.084
GPT teacher head0.387
Teacher spread0.303 · 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