United States Environmental Protection Agency Solid Waste and Emergency Response (5102G) EPA 542-B-99-003 June 1999 www.epa.gov/tio clu-in.org
Bibliographic record
Abstract
Page Number in Guide] Technology Type Media Contaminants Soil GroundWater Organics Pesticides/ Herbicides Metals Radionuclides Explosives GENERAL INFORMATION 1998 United StatesMarket for [1] q The Advancement of Phytoremediation as an Innovative Environmental Technology for Stabilization, Remediation, or Restoration of Contaminated Sites in Canada: A Discussion Paper [2] q Bioremediation and Phytoremediation Glossary [2] q A Citizen's Guide to Phytoremediation [2] EPA 542-F-98-011 qqqqq q Compost-Enhanced Phytoremediation of Contaminated Soil [2] EPA 530-R-98-008 [2] Title Document Ordering Number [Abstract Page Number in Guide] Technology Type Media Contaminants Soil GroundWater Organics Pesticides/ Herbicides Metals Radionuclides Explosives x [3] DE96015254 q Phytoremediation [3] EPA 625-K-96-001 q Phytoremediation [3] q Phytoremediation: A Clean Transition from Laboratory to Marketplace? [3] Phytoremediation: A New Technology Gets Ready to Bloom [3] q q Phytoremediation Field Demonstrations in the U.S. EPA SITE Program [4] q Phytoremediation: It Grows on You [4] q Phytoremediation on the Brink of Commercialization [4] Unspecified Phytoremediation: Technology Overview Report [5] q Phytoremediation: Using Green Plants to Clean Up Contaminated q Remediation Technologies Screening Matrix and Reference Guide [5] Title Document Ordering Number [Abstract Page Number in Guide] Technology Type Media Contaminants Soil GroundWater Organics Pesticides/ Herbicides Metals Radionuclides Explosives xi [5] q q Using Phytoremediation to Clean Up Contamination at Military Installations [6] DE97007971 q Title Document Ordering Number [Abstract Page Number in Guide] Technology Type Media Contaminants Soil GroundWater Organics Pesticides/ Herbicides Metals Radionuc...
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.532 | 0.398 |
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".