MétaCan
Menu
Back to cohort
Record W136010827 · doi:10.7202/706114ar

Measure of agreement between experts on apple damage assessment

2005· article· en· W136010827 on OpenAlexfundvenueaboutno aff
Charles Vincent, J. Hanley

Bibliographic record

VenuePhytoprotection · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsnot available
FundersAgriculture and Agri-Food Canada
KeywordsTarnished plant bugMiridaeCurculioContext (archaeology)BiologyPEST analysisLygusHemipteraIntegrated pest managementCurculionidaeToxicologyHorticultureAgronomyEcology

Abstract

fetched live from OpenAlex

Although damage evaluation is an important and frequent exercise in economic entomology, there are no quantitative studies on inter-rater agreement of experts. In this experiment conducted during the 50th New York, New England and Canadian Pest Management Conference, four teams of experts independently estimated the damage on 200 apples at harvest. The participants identified 22 types of damage caused by insects, 8 by diseases, and 8 related to other causes. For each type of damage an average measure of agreement was calculated. The lowest average agreements were found in plum curculio (Conotrachelus nenuphar) [Coleoptera : Curculionidae] damage (71.8%), tarnished plant bug (Lygus lineolaris) [Hemiptera : Miridae] damage (83.2%), and by early lepidoptera damage (87.1%). The usefulness of inter-rater agreement experiments is discussed in the context of many situations pertaining to crop protection.

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)0.109
metaresearch head score (Gemma)0.202
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score0.576

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1090.202
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.002
Science and technology studies0.0020.002
Scholarly communication0.0020.003
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.024
GPT teacher head0.251
Teacher spread0.228 · 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
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

Citations2
Published2005
Admission routes3
Has abstractyes

Explore more

Same venuePhytoprotectionSame topicInsect-Plant Interactions and ControlFrench-language works237,207