Shape, size, spatial distribution and composition of garnet crystals in highly deformed gneiss of the Otter Lake area, Québec, and a model for garnet crystallization
Bibliographic record
Abstract
Abstract Garnet–biotite–(sillimanite) gneiss (∼700 °C, 7 kbar) of the Otter Lake area in the Western Grenville Province (Canadian Shield) occurs as granitic gneiss (group 4) that forms a large part of the Otter Complex, and as widely distributed, more heterogenous metasedimentary gneiss (group 2). In one sample of group 4 gneiss (Qtz25Pl34Kfs28Bt10Grt2.5Sil1) the true diameter (determined by serial grinding) of subhedral garnet crystals ranges from 0.2 to 3.0 mm, with a mode at 1.0 mm. Nearest‐neighbour measurements in this sample, and in surfaces of nine additional samples (all <5% garnet) confirm that garnet crystals are distributed mainly at random; slight clustering was detected in two samples. In one sample of group 4 gneiss, microprobe analyses on sections through crystal centres (obtained by serial slicing), reveal that small crystals and margins to large crystals contain more Fe and Mn and less Mg than the broad central regions of large crystals. Based on these and previous results, together with theoretical considerations, a crystallization model is proposed, in which, (i) garnet was produced by the continuous reaction, Ms + Bt + Qtz → Grt + Kfs + H2O, (ii) nucleation occurred by the random selection of randomly distributed Ms–Bt–Qtz triple junctions, (iii) the rate of linear growth remained constant, and (iv) as temperature increased, the rate of nucleation first increased slowly, then remained nearly constant, and finally declined. Within‐population compositional homogenization was followed, on cooling, by local Fe–Mg–Mn exchange with biotite.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".