MétaCan
Menu
Back to cohort

Seeking alternatives to probit 9 when developing treatments for wood packaging materials under ISPM No. 15

2011· article· en· W2111376573 on OpenAlexaff
Robert A. Haack, Adnan Uzunovic, Kelli Hoover, J. A. Cook

Bibliographic record

VenueEPPO Bulletin · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsFPInnovations
Fundersnot available
KeywordsFumigationPhytosanitary certificationToxicologyPEST analysisEnvironmental sciencePulp and paper industryBiologyComputer scienceHorticultureEngineering

Abstract

fetched live from OpenAlex

ISPM No. 15 presents guidelines for treating wood packaging material used in international trade. There are currently two approved phytosanitary treatments: heat treatment and methyl bromide fumigation. New treatments are under development, and are needed given that methyl bromide is being phased out. Probit 9 efficacy (100% mortality of at least 93 613 test organisms) has been suggested as an evaluation criterion for new wood treatments, and is based on fruit fly research. We question requiring probit 9 efficacy for wood pests (insects, nematodes and fungi) and discuss challenges to meeting this requirement. Instead, we suggest a 3‐step, laboratory‐based alternative approach. Step 1 involves laboratory experiments (screening) to estimate the lethal dose for the most tolerant stage of each target pest. We consider each infested piece of wood as an experimental unit, not the individual pests, to avoid pseudoreplication. Step 2 requires replicated experiments (with no survivors) at the estimated lethal dose. We suggest a minimum sample size of 60 experimental units, which achieves 0.95 statistical reliability at the 95% confidence level. Step 3 entails studies under simulated operational conditions using wood samples similar in size to wood packaging material and infested to levels that reflect field conditions.

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)0.059
metaresearch head score (Gemma)0.152
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.059
Threshold uncertainty score0.310

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0590.152
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0030.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0220.004

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 head0.029
GPT teacher head0.238
Teacher spread0.209 · 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 designTheoretical or conceptual
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

Citations24
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueEPPO BulletinSame topicForest Insect Ecology and ManagementFrench-language works237,207