TRACES OF EFFECTS OF AClD RAlN (SEDIMENTATION) IN THE RE-DISSOLUTION OF
Bibliographic record
Abstract
coves carstiques d'Hungria presentaven fenornens de redissolució, els quals no havien estat visibles en aquestes coves 5-10 anys abans. Aquestes deforrnacions inqüestionablernent es deuen als efec-tes corrosius de les aigües carstiques que alimenten els esrnentats espeleoternes. Arnb la intenció de clarificar les causes d'aquest efecte, els rneus cornpanys i jo rnateix cornencarern les investiga-cions no tan SOIS a Hungria sinó tarnbé en coves de Txecoslovaquia, Rumania, Bulgaria, lugoslavia i Austria. Fou possible establir que I'extensió del fenornen es universal a Europa Central, encara que en diversos graus depenent de les particulars condicions naturals de cada cova. Signes de la sindrome de degradació recent dels espeleoternes: craters irregulars de voreres agudes i dentades; calderes arnb els costats soscavats; solcs de drenatge poc fondos, arnb voreres tallants; redissolució superficial de I'espeleoterna en la zona d'esquits produits per degotarnents des d'una certa altura; sovint, el subseQüent reblanirnent del material dels espeleotemes, que presen-ten, aixi, un aspecte crernós. Les investigacions que he realitzat fins ara indiquen que una gran gruixa de la coberta edafica bioactiva i perrneable que reposa sobre la roca carstificable, aixi corn la rnajor profunditat de les arrels de la rnacrovegetació (arbres de fulla caduca) desenvolupada sobre I'esrnentat sol, són res-
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".