Apatite Chemical Compositions from Acadian-Related Granitoids of New Brunswick, Canada: Implications for Petrogenesis and Metallogenesis
Bibliographic record
Abstract
The geochemistry of apatite crystals from fifteen fertile and infertile Acadian-related granitoids of New Brunswick (Canada) was studied in situ, using electron microprobe and laser ablation-inductively coupled plasma-mass spectrometry to further investigate petrogenesis and fertility index among these intrusions. The results indicate a clear geochemical contrast between barren and mineralized samples where apatite grains from barren intrusions are the most hydrous (OH > 0.3 wt. %), with lowest Mn (<1700 ppm), Fe (<800 ppm), and Sn (<0.01 ppm). In contrast, apatite grains from Cu-Mo related intrusions are distinguished by higher Cl (>0.1 wt. %), (La/Yb)N ratios of 21.17, (Eu/Eu*)N ratios of 0.30, and LREE/HREE ratios of 6.03. Apatites from Sn-W related magmatic suites have the highest F (>3 wt. %), Mn (>5350 ppm), Fe (>2200 ppm), Y (>4900 ppm), Sn (>2 ppm), and the lowest Cl (<0.01 wt. %), Sr (<60 ppm), U (<18 ppm), Th (<29 ppm), (Eu/Eu*)N ratios (<0.01), and (La/Yb)N ratios (<0.88). Lastly, apatite grains from Mo-bearing systems have the lowest SiO2 (<0.4 wt. %), Sr (<33 ppm), Th (<28 ppm), a moderate Mn (~3800 ppm), Y (~3500 ppm), and highest FeOt (<0.9 wt. %). However, the results indicated apatite Mn, Sr, LREE/HREE, and (Eu/Eu*)N ratios as the best fertility indices used for discriminating barren from fertile granite intrusions.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".