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Record W7098057807

NATIONAL CENTER FOR CASE STUDY TEACHING IN SCIENCE Is High Fructose Corn Syrup Bad for the Apple Industry?

2013· article· en· W7098057807 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDiverse Educational Innovations Studies
Canadian institutionsnot available
Fundersnot available
KeywordsApple treeQuarter (Canadian coin)CropHobbyBeekeepingPhone
DOInot available

Abstract

fetched live from OpenAlex

Dad snapped shut his cell phone and his shoulders slumped. “Now we’ve got a real problem, ” he sighed. Life as an apple farmer in Wenatchee, Washington, could be challenging, but Dad was looking particularly depressed. “What is it now? ” Bruce asked. “Seems that the last beekeeper in the area has lost almost all of his hives, ” Bruce’s dad replied. After a semester of introductory entomology at Washington State University and a childhood spent in an apple orchard, Bruce knew that this was bad. Bees were necessary to pollinate apple trees to produce the fruit. They pollinated over 130 different food crops, such as berries, beans, nuts, melons, and tree fruit. In fact, bees were responsible for over $15 billion in agricultural products in the United States alone. Without bees, there would be none of these foods. And that included apples—which were paying for Bruce’s college education! Bruce thought for a moment. “Can you call anyone from outside the area? ” he asked. “If we can find someone—but, even if we could, it might be too late. We only have a window of a week for pollination,” Bruce’s dad answered. “With the loss of so many hives around here, beekeepers from outside the area might be reluctant to come up here.” Bruce pondered this. Colony Collapse Disorder (CCD), the phrase used to describe the unexplained death or disappearance of a hive, could have over 60 different factors involved. Pesticides and herbicides used in the fields,

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 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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.076
GPT teacher head0.323
Teacher spread0.247 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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
Published2013
Admission routes1
Has abstractyes

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