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Record W3165081356 · doi:10.21061/aaec-238np

Impacts of COVID-19 on U.S. aquaculture, aquaponics, and allied businesses located in the USDA North Central Aquaculture Region: Quarter 1 Results March 23, 2020 to April 10, 2020

2021· report· en· W3165081356 on OpenAlexaboutno aff
Matthew A. Smith, Jonathan van Senten, Carole R. Engle, Charles Clark, Shannon Fluharty, Michael H. Schwarz

Bibliographic record

Venuenot available
Typereport
Languageen
FieldAgricultural and Biological Sciences
TopicInnovations in Aquaponics and Hydroponics Systems
Canadian institutionsnot available
Fundersnot available
KeywordsAquacultureQuarter (Canadian coin)AquaponicsCoronavirus disease 2019 (COVID-19)FisheryGeographySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakFish <Actinopterygii>BiologyOutbreakVirologyArchaeologyMedicineInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

In response to the coronavirus disease (COVID-19), Virginia Tech and the Ohio State University collected information about how aquaculture/aquaponics farms and allied businesses have been affected by the COVID-19 pandemic. A survey was conducted at the conclusion of the first quarter of 2020 to capture and quantify these impacts and effects. The survey will be distributed once per quarter throughout 2020, to capture the evolving effects of coronavirus disease (COVID-19) on your farm or business. This publication summarizes the first set of results for the 1st quarter of 2020.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.129
Threshold uncertainty score0.257

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
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 head0.048
GPT teacher head0.288
Teacher spread0.240 · 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 designObservational
Domainnot available
GenreOther

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

Citations0
Published2021
Admission routes1
Has abstractyes

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