ESTIMATES OF THE NUMBERS AND AREAS OF ACIDIC LAKES IN NOVA SCOTIA
Bibliographic record
Abstract
and pH isopleth maps were consulted to estimate acidified and acid sensitive lakes. Assuming that granitic or metamorphic bedrock only very slowly produce add neutralizing ions, we estimate that 78 % of the lakes (65%of la ke area) would, in the absence of moderating influences of surficial geology and marine aerosols,be susceptible to acidifjcation. When all sources of acid neutralizing capacity are indirectly considered via examination of pH isopleths drawn from lake chemistry, we estimate that 16 % of the lakes \\26%01 lake area) have zero alkalinity. and that 69 % of the lakes (80 % of lake area) have < 50 J,teq l- alkalinity. En Nouvelle-Ecosse iI ya 6674 lacs ayant une superficie au dela d'un hectare. avec une superficie totale de 2255 km2 • On a consulte des cartes geologiques ainsi que des cartes d'isoplethes de pH, en but d'obtenir une estimation des lacs acidifies ainsi que des lacs sensibles a I'acide. Supposant que Ie fond de roche granitique ou metamorphique libere des ions qui neutralisent I'acide tres lentement, nous estimons que 78 % des lacs (85 % des superficies) seraient predisposes it I'acidification, dans I'absence d'influences moderantes de Ia geologie superficielle. Quand on donne leurs poids a toutes les sources demontrant la capacite de neutraliser I'acide, par Ie biais d'inspection des isoplethes de pH des lacs, nous estimons que 16 % des lacs (26 % de Ia superficie totale) ont nulle alcalinite, et que 68% des lacs (80 % de la superficie totale) ont une mesure d'alcalinite de 50 peq l- '.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".