Bibliographic record
Abstract
there has been increased interest indeveloping thermal processes to replace chemicalfumigation as quarantine and phytosanitary treatmentsfor preshipment and export commodities, primarily due to the imminent loss of methyl bromide (Federal Clean Air Act, 1990) and increasing public concerns over chemical residues on foods. Methyl bromide (MeBr) is a relatively inexpensive and effective fumigant and has traditionally been used to control many insect pests, including quarantine insects such as the codling moth (CM). MeBr, however, has been associated with ozone depletion. The U.S. Environmental Protection Agency, under the Montreal Protocol (UNEP, 1995), has mandated a sharp reduction of MeBr use between 1999 and 2005 and cessation of its production and importation by 2005 (Federal Clean Air Act, 1990). This will likely force the United States multi-billion dollar fruit and nut industry to abandon the fumigant for the postharvest control of pests. Thus, alternative control processes need to be developed to replace current treatment practices for both the domestic and international markets. Reports by many researchers have shown that different thermal treatment methods alone, or combined with cold storage or a controlled atmosphere, can control insect pests in selected host commodities (Sokhansanj et al., 1990,
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.180 | 0.092 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".