Magnetic characterisation of magnetite and hematite from the Blötberget apatite – iron oxide deposits (Bergslagen), south-central Sweden
Bibliographic record
Abstract
Rock magnetic measurements were carried out on drill core material and hand specimens from the Blötberget apatite – iron oxide deposit in the Bergslagen ore province, south-central Sweden, to characterise their magnetic properties. Measurements included several kinds of magnetic susceptibility and hysteresis parameters. Petrographic and scanning electron microscopy were used to independently identify and quantify the amount and type of magnetite and hematite. Two hematite-rich samples were studied with laser ablation inductively coupled plasma mass spectrometry to quantify the trace element chemistry in hematite and investigate the potential influence of trace elements on magnetic properties. Three aspects of this study are noteworthy. (1) Hematite-rich samples display strong anisotropy of magnetic susceptibility, which is likely to affect the appearance and modelling of magnetic anomalies. (2) The magnitude-drop in susceptibility across Curie and Néel temperature transitions shows significant correlation with the respective weight percentage of magnetite and hematite. Temperature-dependent magnetic susceptibility measurements can therefore be used to infer the amounts of both magnetite and hematite. (3) Observations of a strongly depressed Morin transition at approximately −60 to −70 °C (200 to 210 K) are made during low-temperature susceptibility measurements. This anomalous Morin transition is most likely related to trace amounts of V and Ti that substitute for Fe in the hematite. When taken together, these magnetic observations improve the understanding of the magnetic anomaly signature of the Blötberget apatite – iron oxide deposits and may potentially be utilised in a broader context when assessing similar (Paleoproterozoic) apatite – iron oxide systems.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".