Bibliographic record
Abstract
从全球视野分析研究了世界岩浆铜镍硫化物矿床的大地构造分布和成岩成矿类型,特别是通过上世纪末新发现的加拿大Voisey＇s Bay矿床与俄罗斯Noril＇sk等世界级矿床特征的对比研究,突出强调了大火成岩省（LIPs）对大规模岩浆硫化物矿床形成的意义,从更加宏观的角度审视了世界级岩浆硫化物矿床形成的地质背景和岩浆作用条件,为中国金川等岩浆Cu-Ni-PGE硫化物矿床的深入研究提供了参照背景.评述分析了当代岩浆硫化物矿床成矿研究中,幔源岩浆中硫化物液相不混溶（熔离）的演化轨迹,对岩浆萃取地壳中的硫改变硫化物饱和度促成不混溶作用发生的可能性和条件进行了探讨,进一步讨论了岩浆演化过程中,亲铜元素（Ni、Cu、Co、Pt和Pd等）进入硫化物液相成为金属硫化物或先期进入先结晶的橄榄石、辉石矿物成为氧化物的物理化学行为,并通过加拿大Sudbury陨石撞击构造成因矿床复合热液对硫化物矿体形成贡献的讨论,提出了热液作用对岩浆硫化物矿床成矿的可能贡献.分析判断了中国岩浆Cu-Ni-PGE硫化物矿床的成矿特点和金川超大型岩浆Cu-Ni-PGE矿床外围的找矿潜力.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".