Enzo Caraballo, Georges Beaudoin, Sarah Dare, Dominique Genna, Sven Petersen, Jorge M.R.S. Relvas, Stephen J. Piercey
{"title":"火山岩块状硫化物矿床中黄铜矿微量元素组成的变化及其对物源识别的意义","authors":"Enzo Caraballo, Georges Beaudoin, Sarah Dare, Dominique Genna, Sven Petersen, Jorge M.R.S. Relvas, Stephen J. Piercey","doi":"10.5382/econgeo.5020","DOIUrl":null,"url":null,"abstract":"Chalcopyrite from 51 volcanogenic massive sulfide (VMS) and sea-floor massive sulfide (SMS) deposits from six lithostratigraphic settings was analyzed for trace elements by laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) to evaluate its potential as an indicator mineral for exploration. Partial least squares discriminant analysis (PLS-DA) results reveal that chalcopyrite from different lithostratigraphic settings has different compositions reflecting host rock assemblages and fluid composition. Three random forest (RF) classifiers were developed to distinguish chalcopyrite from the six lithostratigraphic settings with a divisive approach. This method, which primarily classifies according to the major host-rock affinity and subsequently according to VMS settings, yielded an overall accuracy higher than 0.96 on test data. The model validation with literature data having the same elements required by the models yielded the highest accuracies (>0.90). In validation using published data with missing elements, the accuracy is moderate to high (0.60–1); however, the performances decrease significantly (<0.50) when the most important elements are missing. Similarly, RF regression models developed using all sets of analyzed elements to determine ccp/(ccp + sp) ratio (ccp = chalcopyrite; sp = sphalerite) in chalcopyrite within a single VMS setting reported high performances, thus showing a potential to predict the Cu/Zn ratio (Cu-rich vs. Zn-rich) of the mineralization based on chalcopyrite composition. This study demonstrates that trace element concentrations in chalcopyrite are primarily controlled by lithotectonic setting and can be used as predictors in an RF classifier to distinguish the different VMS subtypes.","PeriodicalId":11469,"journal":{"name":"Economic Geology","volume":"43 1","pages":"0"},"PeriodicalIF":5.5000,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Trace Element Composition of Chalcopyrite from Volcanogenic Massive Sulfide Deposits: Variation and Implications for Provenance Recognition\",\"authors\":\"Enzo Caraballo, Georges Beaudoin, Sarah Dare, Dominique Genna, Sven Petersen, Jorge M.R.S. Relvas, Stephen J. Piercey\",\"doi\":\"10.5382/econgeo.5020\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Chalcopyrite from 51 volcanogenic massive sulfide (VMS) and sea-floor massive sulfide (SMS) deposits from six lithostratigraphic settings was analyzed for trace elements by laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) to evaluate its potential as an indicator mineral for exploration. Partial least squares discriminant analysis (PLS-DA) results reveal that chalcopyrite from different lithostratigraphic settings has different compositions reflecting host rock assemblages and fluid composition. Three random forest (RF) classifiers were developed to distinguish chalcopyrite from the six lithostratigraphic settings with a divisive approach. This method, which primarily classifies according to the major host-rock affinity and subsequently according to VMS settings, yielded an overall accuracy higher than 0.96 on test data. The model validation with literature data having the same elements required by the models yielded the highest accuracies (>0.90). In validation using published data with missing elements, the accuracy is moderate to high (0.60–1); however, the performances decrease significantly (<0.50) when the most important elements are missing. Similarly, RF regression models developed using all sets of analyzed elements to determine ccp/(ccp + sp) ratio (ccp = chalcopyrite; sp = sphalerite) in chalcopyrite within a single VMS setting reported high performances, thus showing a potential to predict the Cu/Zn ratio (Cu-rich vs. Zn-rich) of the mineralization based on chalcopyrite composition. This study demonstrates that trace element concentrations in chalcopyrite are primarily controlled by lithotectonic setting and can be used as predictors in an RF classifier to distinguish the different VMS subtypes.\",\"PeriodicalId\":11469,\"journal\":{\"name\":\"Economic Geology\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":5.5000,\"publicationDate\":\"2023-09-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Economic Geology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5382/econgeo.5020\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOCHEMISTRY & GEOPHYSICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Economic Geology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5382/econgeo.5020","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOCHEMISTRY & GEOPHYSICS","Score":null,"Total":0}
Trace Element Composition of Chalcopyrite from Volcanogenic Massive Sulfide Deposits: Variation and Implications for Provenance Recognition
Chalcopyrite from 51 volcanogenic massive sulfide (VMS) and sea-floor massive sulfide (SMS) deposits from six lithostratigraphic settings was analyzed for trace elements by laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) to evaluate its potential as an indicator mineral for exploration. Partial least squares discriminant analysis (PLS-DA) results reveal that chalcopyrite from different lithostratigraphic settings has different compositions reflecting host rock assemblages and fluid composition. Three random forest (RF) classifiers were developed to distinguish chalcopyrite from the six lithostratigraphic settings with a divisive approach. This method, which primarily classifies according to the major host-rock affinity and subsequently according to VMS settings, yielded an overall accuracy higher than 0.96 on test data. The model validation with literature data having the same elements required by the models yielded the highest accuracies (>0.90). In validation using published data with missing elements, the accuracy is moderate to high (0.60–1); however, the performances decrease significantly (<0.50) when the most important elements are missing. Similarly, RF regression models developed using all sets of analyzed elements to determine ccp/(ccp + sp) ratio (ccp = chalcopyrite; sp = sphalerite) in chalcopyrite within a single VMS setting reported high performances, thus showing a potential to predict the Cu/Zn ratio (Cu-rich vs. Zn-rich) of the mineralization based on chalcopyrite composition. This study demonstrates that trace element concentrations in chalcopyrite are primarily controlled by lithotectonic setting and can be used as predictors in an RF classifier to distinguish the different VMS subtypes.
期刊介绍:
The journal, now published semi-quarterly, was first published in 1905 by the Economic Geology Publishing Company (PUBCO), a not-for-profit company established for the purpose of publishing a periodical devoted to economic geology. On the founding of SEG in 1920, a cooperative arrangement between PUBCO and SEG made the journal the official organ of the Society, and PUBCO agreed to carry the Society''s name on the front cover under the heading "Bulletin of the Society of Economic Geologists". PUBCO and SEG continued to operate as cooperating but separate entities until 2001, when the Board of Directors of PUBCO and the Council of SEG, by unanimous consent, approved a formal agreement of merger. The former activities of the PUBCO Board of Directors are now carried out by a Publications Board, a new self-governing unit within SEG.