Geology, geochemistry, and geochronology of the Laozuoshan gold deposit, Heilongjiang Province, Northeast China: implications for multiple gold mineralization events and geodynamic setting
Bibliographic record
Abstract
The Laozuoshan gold deposit, located in the central part of the Jiamusi Massif, is hosted by the contact zone between granitic complex and Proterzoic strata. In this study, we present the results of geochronology and geochemistry of ore-related granodiorite and diorite porphyry, and hydrothermal sericite 40 Ar/ 39 Ar dating. The granodiorite and diorite porphyry in the Laozuoshan gold deposit are calc-alkaline and high-K (calc-alkaline) series, which are enriched in LREE and LILE and depleted in HFSE, with no depletion of Eu. The geochronology data show that zircon U–Pb ages of the granodiorite and diorite porphyry are ∼262 Ma and ∼105 Ma, respectively. The sericite 40 Ar/ 39 Ar ages are ∼194 Ma and ∼108 Ma. On the basis of previous researches, ore geology and geochronology studies show that the Laozuoshan gold deposit underwent at least two gold mineralization events. We suggest that the first one, which was related to skarnization, resulted from the collision between the Jiamusi and Songnen Massifs in Late Permian. The subsequent gold mineralization resulted from the subduction of the paleo-Pacific Plate in Early Cretaceous.
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 | 0.001 | 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".