A Bayesian Depth-Confidence Model for Deep Orogenic Gold Exploration Using Logistic Survival Functions Calibrated to the Fault-Valve Mechanism
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| Natura: | Recurso digital |
| Lingua: | inglese |
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2026
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| _version_ | 1866901743307063296 |
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| author | Chen, Ruqing |
| author_facet | Chen, Ruqing |
| contents | <p>We develop a Bayesian posterior probability model for assessing the likelihood that a drill-core intercept of gold mineralization at depth belongs to a super-large (≥100 t Au) orogenic deposit system. Unlike previous exponential-decay formulations, we employ logistic survival functions calibrated to the fault-valve mechanism (Sibson, 1988; 2001), with physically motivated critical closure depths (Hc) that represent the statistical half-survival depth for each system class. All probabilities are defined within a unified probability space: a targeted exploration site with surface anomalies, where the prior P₀(Large) = 0.01 represents the empirical base rate. The model shows that at 2500 m depth, the posterior confidence is 65–100% (central: 97.3%), depending on the steepness parameter kS. The logistic formulation eliminates three vulnerabilities of exponential models: (1) zero-depth intercept bias, (2) conflation of modern depth with paleo-crustal position, and (3) circular reasoning via hard-coded decay constants. The critical closure depth Hc,S = 1000 m is derived from first principles: Hc = Hpaleo,crit − Δerosion ≈ 6000 − 5000 = 1000 m. Source code and data: https://github.com/Ruqing1963/bayesian-depth-confidence-model</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18890870 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | A Bayesian Depth-Confidence Model for Deep Orogenic Gold Exploration Using Logistic Survival Functions Calibrated to the Fault-Valve Mechanism Chen, Ruqing deep exploration orogenic gold Bayesian confidence logistic survival function fault-valve mechanism critical closure depth brittle-ductile transition Archean greenstone belt mineral exploration depth-dependent filtering Earth Sciences Mathematical Geosciences Economic Geology <p>We develop a Bayesian posterior probability model for assessing the likelihood that a drill-core intercept of gold mineralization at depth belongs to a super-large (≥100 t Au) orogenic deposit system. Unlike previous exponential-decay formulations, we employ logistic survival functions calibrated to the fault-valve mechanism (Sibson, 1988; 2001), with physically motivated critical closure depths (Hc) that represent the statistical half-survival depth for each system class. All probabilities are defined within a unified probability space: a targeted exploration site with surface anomalies, where the prior P₀(Large) = 0.01 represents the empirical base rate. The model shows that at 2500 m depth, the posterior confidence is 65–100% (central: 97.3%), depending on the steepness parameter kS. The logistic formulation eliminates three vulnerabilities of exponential models: (1) zero-depth intercept bias, (2) conflation of modern depth with paleo-crustal position, and (3) circular reasoning via hard-coded decay constants. The critical closure depth Hc,S = 1000 m is derived from first principles: Hc = Hpaleo,crit − Δerosion ≈ 6000 − 5000 = 1000 m. Source code and data: https://github.com/Ruqing1963/bayesian-depth-confidence-model</p> |
| title | A Bayesian Depth-Confidence Model for Deep Orogenic Gold Exploration Using Logistic Survival Functions Calibrated to the Fault-Valve Mechanism |
| topic | deep exploration orogenic gold Bayesian confidence logistic survival function fault-valve mechanism critical closure depth brittle-ductile transition Archean greenstone belt mineral exploration depth-dependent filtering Earth Sciences Mathematical Geosciences Economic Geology |
| url | https://doi.org/10.5281/zenodo.18890870 |