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Record W3049305687 · doi:10.1201/9781003067900-22

Sampling Arthropods in Livestock Management Systems

2020· book-chapter· en· W3049305687 on OpenAlex
Timothy J. Lysyk, Roger D. Moon

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

Venuenot available
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Pest Control Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsLivestockSampling (signal processing)GeographyEnvironmental scienceEnvironmental resource managementEcologyBiologyComputer scienceComputer vision

Abstract

fetched live from OpenAlex

A North American livestock industries are diverse and of high value, consisting of very different animals and industries: beef cattle are raised for calves, meat, and leather; dairy animals for milk and veal; swine for pork; poultry for eggs and meat; and sheep for meat and wool. R. C. Axtell classifies livestock production systems as pasture or range, outdoor confined, and indoor confined. Detailed descriptions of the biology, taxonomy, host range, and management of livestock pests are available and should be consulted before starting a sampling program. Thresholds for many parasites in livestock production systems remain to be studied. Techniques for sampling arthropods in livestock systems have been previously summarized. Various livestock pests have free-living stages or periods in their life cycle. A diversity of domestic animals and management systems constitute livestock industries in Canada and the US As in other agricultural sectors, a variety of sampling approaches have been used to achieve management and research objectives.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.960
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.042
GPT teacher head0.223
Teacher spread0.180 · 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

Quick stats

Citations9
Published2020
Admission routes1
Has abstractyes

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