Thematic Integration of Spatial Data Sets to Delineate Favourable Zones for Uranium Exploration in Gangpur Basin and Parts of Kunjar and Darjing Basins, Odisha
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Surface exploration techniques have been key contributors in discovering mineral deposits over the past three decades. However, in the last decade there has been a growing emphasis on integrating remote sensing, geological, geophysical and geochemical exploration techniques to compliment them in identifying concealed deposits. Successful integrated exploration requires putting mappable petrophysical property contrasts in terms of geological and geochemical process that could be associated with different mineralisation environment. The Precambrian Gangpur basin comprising volcanic free sedimentary sequence is considered as a potential geological setting for hosting uranium mineralisation. The Gangpur basin with metasediments of low to medium metamorphic grade classified as the Gangpur Group are known for hosting manganese, limestone and lead-zinc deposits. Uranium mineralization is reported in limonitic carbonaceous phyllite and sheared quartzite of Kumarmunda Formation at Jhamankele-Bhalulata areas. Several uranium anomalies have been associated with gossan at Kaedarpani, Jamdra and in ferruginised laterite at Badekachar, Jarmal, Jhagarpur, Kadorpani, Karamabahal, Tetelkela & Kumtinunda. In the present study geological, geophysical and remote sensing data sets are processed and integrated with other available data to delineate target zones for uranium exploration. Even though direct detection of uranium mineralisation remains unresolved in exploration strategy, instead it is becoming increasingly instructive to focus on mapping suitable depositional environments. The enhanced satellite imagery is interpreted in terms of thematic layers viz. trend lines, lineaments, faults and geological contacts. The aeromagnetic data is processed and interpreted thematic layers of magnetic breaks and linears from total magnetic intensity (TMI), the reduced to pole (RTP), tilt derivative and amplitude of analytical signal grid images. The radiometric data is processed based on their broad lithology and radio-elemental distribution maps viz. count maps, ratio maps, ternary (%K-eTh-eU) and eU/K – eU/eTh – eU images are generated to aid in mapping uranium favourability zones. The favourability image zones with high eU/K, eU/eTh and eU counts zones are classified into class based on statistics and anomalous high zones are picked up as uranium favourable locales. The thematic layers of geological contacts, lineaments and faults interpreted from satellite imagery, magnetic linears interpreted from aeromagnetic data and uranium favourability zone extracted from Airborne Gamma Ray Spectrometric (AGRS) data are overlaid. Based on spatial association of favourable features few locals are delineated for uranium exploration.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 it