The magnetic susceptibility of soils in Kohgilouye, Iran
Bibliographic record
Abstract
Soil magnetic susceptibility (MS) and Fe were examined for several soils on calcareous parent material, reflecting key climatic conditions and drainage classes in southwestern Iran (Kohgilouye Province). Alfisols, in the eastern and northern parts, contained more pedogenic (citrate dithionite extractable) Fe (up to 60 g kg-1 on a minerogenic basis; 70 % of total Fe, as determined by lithium tetraborate fusion) and poorly crystalline Fe (up to 6 g kg-1 ammonium oxalate extractable) than the Inceptisols in the southern parts. Soil MS (χlf) ranged from 5 to 120 × 10–8 m3 kg-1, with A horizons exhibiting greater values than B horizons, and Alfisols higher than other soils. Pedogenic enhancement of χlf corresponded with preferential leaching of diamagnetics (primarily carbonates), as well as weathering of primary paramagnetics and neoformation of antiferromagnetics. Frequency dependence of MS (χfd), indicating ultrafine superparamagnetics, followed trends similar to χlf. Sequential heating of well-drained samples, from 25 to 500°C, resulted in enhancement of Χ (average of 21%), a ttributed to the conversion of antiferromagnetics to ferrimagnetics; between 500 and 700°C, Χ typically decreased (average of 15%). The Χfd of well-drained soils increased by an average of 5.3 percentiles by 700°C. Gleysolic soils exhibited less weathering (<51% of total Fe), higher proportions of poorly crystalline Fe (>0.15), lower Χlf (<25 × 10–8 m3 kg-1) and Χfd (<2%), as well as greater average enhancements of Χlf (265% at 500°C) and Χfd (8.4 percentiles at 700°C) on heating. Key words: Calcareous, iron oxides, citrate dithionite, ammonium oxalate, frequency dependence, thermal enhancement
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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".