Türkiye Jeoloji Bülteni
Baskıda Olan Kabul Edilmiş Makaleler

Abstract: In recent years, artificial intelligence(AI) models have become routine in geoscience applications ranging from earthquake early warningsystems to landslide susceptibility mapping, subsurface resource modeling, and stratigraphic classification. Out performing traditional methods for predictiveaccuracy, these models increasingly mediate between observation and inference. However, this technical success raises a critical question: does high predictive accuracy reflect true geological understanding` Thispaper draws attention to the risk that the growing predictive capacity of data-driven models may overshadow the interpretive nature of geoscience andthe elucidation of actual geological conditions. Indomains where observations are sparse, uncertainty is structural, and ground truth is limited—such assubsurface interpretation and hazard assessment—models can achieve seemingly high classification accuracy by relying on mechanistically irrelevant proxies. This undermines model transferability andgeological consistency under changing environmental / tectonic conditions. Without rejecting predictivemodeling, this perspective aims to propose a conceptual and semi-formalized "assistant" framework— not introducing a new algorithm but rather a guidingstructure—that integrates geological constraints, interpretable modeling, and post-hoc geological validation to ensure that predictive performance doesnot override geological reasoning. 

Artificial intelligence
explainable AI
geological interpretation
physics-informed machine learning
predictive models

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Abstract: Listvenite-type silica–carbonate metasomatic alteration in the Vezirler ophiolitic mélange (northeastern Kula, western Türkiye) was screened using a lithology-masked Selective PCA workflow and complementary band ratio indices applied to a cloud-free Landsat-7 ETM+ image. Masking reduced spectral mixing from vegetation, alluvium, and non-target lithologies and increased anomaly contrast within a field-verified ROI. Ferric-iron–sensitive PC2 anomalies cluster along carbonatized/silicified serpentinites (CS-Srp) and Fe-oxide-stained silica–carbonate caps (Fscc/Cnz), consistent with hematite coatings documented in the field. Ferrous-iron responsesare comparatively subdued, indicating limited preservation of surface-expressed Fe²+ signatures under pervasive oxidation and overprinting. Hydroxyl-related patterns delineate alteration halos but weaken over strongly silicifiedcaps where diagnostic OH absorption is suppressed. Band-ratio maps (Fe³+: B3/B2; silica: B7/B5; OH-: B5/(B5+ B7)), statistically segmented using μ ± σ thresholds, reproduce first-order PCA patterns and support repeatable anomaly ranking. The results demonstrate a rapid regional screening approach relevant to alteration targeting and natural mineral carbonation analogues, while recognizing inherent limitations of the 30 m resolution, such as false positives in shaded valleys due to topographic effects and spectral dilution from mixed-pixel responses along slope transitions. Future work may integrate ASTER TIR and archival ASTER SWIR scenes acquired prior to 2008, ormodern SWIR/hyperspectral datasets, to improve mineral discrimination.

Band ratios
Crosta-PCA
iron oxides
Kula
Landsat-7 ETM+
listvenite
silica-carbonate alteration
remote sensing

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Abstract: This study presents a comparative investigation of the emplacement conditions for gabbroic intrusion sexposed on Dee and Cecilia islands, located along the South Shetland Islands to the north of the Antarctic Peninsulain Western Antarctica. Crystallization temperatures and emplacement pressures were calculated using two-pyroxene geothermobarometry, and oxygen fugacity conditions were additionally constrained based on Fe–Ti oxide pairs. Petrographically, the Dee intrusions are characterized by fine-grained, holocrystalline porphyritic textures composed of plagioclase, clinopyroxene, orthopyroxene, olivine, and opaque minerals. The Cecilia intrusion displays broadly similar mineral assemblage but coarser-grained holocrystalline granular textures. Plagioclase in the Deeintrusions predominantly exhibits normal zoning, whereas plagioclase crystals in the Cecilia intrusion commonlyshow oscillatory and locally reverse zoning, together with sieve textures and embayment structures. Two-pyroxene geothermobarometric calculations suggest that the Dee intrusions crystallized at temperatures of approximately1,030–1,090 ºC and pressures of 2.5–3.5 kbar, corresponding to relatively shallow upper-crustal emplacement.In contrast, the Cecilia intrusion yields crystallization temperatures of 1,000–1,170 ºC and pressures of 4.5–6.5kbar, consistent with deeper emplacement at mid- to lower-crustal levels. Fe–Ti oxide barometry indicates that bothintrusions crystallized under oxidizing redox conditions, with the Cecilia intrusion recording systematically higheroxygen fugacity values relative to the Dee intrusions.When field, petrographic, and mineral chemistry data are evaluated together, the Dee and Cecilia intrusionsare interpreted to represent mafic magmatic bodies emplaced at different crustal levels within the South Shetland Arc magmatic system. Future geochronological studies will lead the investigation of the timing of emplacementand further assess the relationship between the crustal evolution of these mafic intrusions and the regional tectonic framework.

Gabbro
geothermobarometry
mineral chemistry
petrography
South Shetland Islands