The DTARPS-S analysis starts with 0.9 million TESS Year 1 FFI light curves extracted and preprocessed by the DIAmante project (Montalto+ 2020). ARIMA and TCF are applied and dozens of features provide input into a Random Forest classifier trained towards injected exoplanets (and away from injected eclipsing binaries) to identify 7743 possible transiting systems. A conservative, multistep vetting process then gives 462 high-purity DTARPS-S candidates plus 177 in a Galactic Plane list. DTARPS-S procedure is described in Melton+ 2024a and 2024b with source tables and graphics. See the poster: DIAmante TESS AutoRegressive Planet Search: Overview and Methodology for more immediate details on the procedure. DIAmante TESS AutoRegressive Planet Search (DTARPS) Results from the DTARPS-S Catalog Elizabeth Melton1, Andrew Pellegrino2, Eric Feigelson2, Marco Montalto3, Yash Gondhalekar4 1Rose- Hulman Institute of Technology 2Pennsylvania State University 3 INAF – Osservatorio Astrofisico di Catania 4Birla Institute of Technology and Science Pilani AutoRegressive Planet Search Papers Caceres, G. A., Feigelson, E. D., Babu, J. G., et al., Augoregessive Planet Search: Methodology, 2019, AJ, 158, 2, 57 Caceres, G. A., Feigelson, E. D., Babu, J. G., et al., Autoregressive Planet Search: Application to the Kepler Mission, 2019, AJ, 158, 58 Gondhalekar, Y., Feigelson, E. D., Caceres, G. A., A Study of Two Periodogram Algorithms for Improving the Detection of Small Transiting Planets, 2023, ApJ, 959, 16 Melton, E. J., Feigelson, E. D., Montalto, M., et al., DIAmante TESS AutoRegressive Planet Search (DTARPS). 1. Analysis of 0.9 Million Light Curves, 2024, AJ, 167, 202 Melton, E. J., Feigelson, E. D., Montalto, M., et al., DIAmante TESS AutoRegressive planet Search (DTARPS). 2. Hundreds of New TESS Candidate Exoplanets, 2024, AJ, 167, 203 Melton, E. J., Feigelson, E. D., Montalto, M., et al., DIAmante TESS AutoRegressive planet Search (DTARPS). 3. Understanding the DTARPS-S Candidate Transiting Planet Catalogs, 2024, AJ, in review Montalto, M., et al. A search for transiting planets around FGKM dwarfs and subgiants in the TESS full frame images of the Southern ecliptic hemisphere, 2020, MNRAS, 498, 172 Planetary Occurrence Rates Our careful analysis of ARPS performance on injections, known exoplanets and False Positives, allows us to estimate occurrence rates for TESS FGK. DTARPS-S occurrence rates are consistent with those from Kepler except in the hot Neptune region. Hundreds of hot Neptunes! 1. Training set False Positive Rate of 0.043% is supported by very few known EBs misclassified by the Random Forest. The DTARPS-S Candidates in the Neptune desert have a specificity (True Negative Rate) of 91%. 2. After vetting, there are only 42 known False Positives in the 462-object DTARPS-S Candidate catalog and Galactic Plane list. These include 22 EBs and 5 blended EBs. Comparison with the Prsa et al 2022 catalog of probable eclipsing binaries upheld the high specificity (94%) of the DTARPS methodology. 3. Application of the TRICERATOPS vetting and validation tool suggests the DTARPS-S precision (retrieved fraction) is 50-60%. 4. Reconnaissance spectroscopy of a limited subsample of DTARPS-S Candidates suggests that less than half, and possibly fewer than a third, of the catalog is contaminated by EBs. 5. Planetary occurrence rates estimated from the DTARPS-S Candidates does not exceed estimated from rates obtained from Kepler Confirmed Planets except in the Neptune desert. 6. DTARPS-S planet candidates with radii > 15 R that are likely inflated by stellar heating are largely restricted to insolation fluxes in excess of 300 𝑆𝑆⊕. Future Work ARPS is now being applied to Year 2 TESS data (DTARPS-N) with similar results to DTARPS-S. Application to the full TESS mission dataset, particular ecliptic pole regions is planned (Pellegrino+). ARPS methodology is being improved: XGBoost instead of Random Forest to reduce False Positive rates; improved blended EB