Bibliographic record
Abstract
action research/participatory action research 179, 192-3 definitions of 178 functions of 177 qualitative/quantitative research tools in 179-80 deductive 180-81 descriptive 180 predictive 181 reflective 181 agriculture 152, 198 import/export of 235-7 related water flows 232, 241-3 analytical hierarchy process (AHP) 131 anthropology environmental 81 Aristotle view of rhetoric 35 Association for the Study of Peak Oil (ASPO) 201 Australia 104, 417 statistical local areas (SLA) 417 virtual water exports of 241 Berkes, Fikert 58 biodiversity 54, 231 anthropogenic stresses on 66, 71 conservation 81 loss of 122 Blue Crab Technical Advisory Committee 89 bovine spongiform encephalopathy (BSE) 24 Brazil 242 exports of 235 virtual water exports of 234 green 237 virtual water imports of 241 Brent-Spar oil platform disposal of 24 Bullard, Clark 207 Canada 182, 210-11, 213-14, 232, 504 blue water exports of 235 green water exports of 237 Nova Scotia 104 oil and gas industry of 210-12, 214 tar sands 211-13 Toronto 412 virtual water exports of 234 capital 135, 140 financial 140 health 140 human 136, 139, 375 investment 198, 375-6 social 132, 135-6, 141, 349 stocks 8 carbon capture and sequestration (CCS) 221 carbon dioxide (CO 2 ) 415, 418, 420-21 direct 416-18 use of OLS regression in prediction of 419 emissions 231, 243, 285, 305, 309, 408-9, 412, 420 reduction of 376 urban metabolism paradigm 408, 411-15 indirect 416, 418 urban-rural contrast 417-18, 422
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.018 |
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; both teacher heads agree on what is shown here.
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".