Données de thèse – Géologie, hydrothermalisme et évolution tectonométamorphique du gisement Amaruq : implications pour les minéralisations aurifères de la partie occidentale de la Province de Churchill, Nunavut (Annexes A à H et Appendices D et G).
Bibliographic record
Abstract
Ce jeu de données regroupe l’ensemble des données analytiques et de terrain associé aux Annexes A à H et aux Appendices D et G de la thèse de doctorat portant sur le gisement aurifère Amaruq (Nunavut, Canada) qui a été déposée en mai 2024 à l’Université du Québec à Montréal. Les données ont été acquises dans le cadre de cette étude multidisciplinaire et comprennent : - des données géochronologiques (U–Pb et 40Ar/39Ar), - des données géochimiques sur roche totale, - des données de chimie minérale (microsonde), - des analyses LA-ICP-MS sur phases métalliques, - des mesures structurales de terrain, - des inventaires d’échantillons (affleurements et forages). Ces données soutiennent l’interprétation stratigraphique, tectonometamorphique et métallogénique présentée dans le manuscrit.
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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.034 | 0.030 |
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".