feat: update CMU-TimeSeries metadata

Author: dshemetov

model-metadata/CMU-TimeSeries.yml

@@ -4,51 +4,19 @@ model_name: "AR ensemble with auxiliary data"
 model_abbr: "TimeSeries"
 model_version: "1.0"
 model_contributors:
-    [
-        {
-            "name": "Logan Brooks",
-            "affiliation": "UC Berkeley",
-            "email": "[email protected]",
-        },
-        {
-            "name": "Dmitry Shemetov",
-            "affiliation": "Carnegie Mellon University",
-            "email": "[email protected]",
-        },
-        {
-            "name": "Nat DeFries",
-            "affiliation": "Carnegie Mellon University",
-            "email": "[email protected]",
-        },
-        {
-            "name": "Addison Hu",
-            "affiliation": "Carnegie Mellon University",
-            "email": "[email protected]",
-        },
-        {
-            "name": "David Weber",
-            "affiliation": "Carnegie Mellon University",
-            "email": "[email protected]",
-        },
-        {
-            "name": "Daniel McDonald",
-            "affiliation": "University of British Columbia",
-            "email": "[email protected]",
-        },
-        {
-            "name": "Ryan Tibshirani",
-            "affiliation": "UC Berkeley",
-            "email": "[email protected]",
-        },
-    ]
-website_url: "https://github.com/cmu-delphi/flu-hosp-forecast/"
-repo_url: "https://github.com/cmu-delphi/flu-hosp-forecast/"
+  [
+    { "name": "Logan Brooks", "affiliation": "UC Berkeley", "email": "[email protected]" },
+    { "name": "Dmitry Shemetov", "affiliation": "Carnegie Mellon University", "email": "[email protected]" },
+    { "name": "Nat DeFries", "affiliation": "Carnegie Mellon University", "email": "[email protected]" },
+    { "name": "David Weber", "affiliation": "Carnegie Mellon University", "email": "[email protected]" },
+    { "name": "Daniel McDonald", "affiliation": "University of British Columbia", "email": "[email protected]" },
+    { "name": "Ryan Tibshirani", "affiliation": "UC Berkeley", "email": "[email protected]" },
+  ]
+website_url: "https://github.com/cmu-delphi/exploration-tooling/"
+repo_url: "https://github.com/cmu-delphi/exploration-tooling/"
 license: "CC-BY-4.0"
 designated_model: true
 team_funding: "Centers for Disease Control and Prevention Awards: U011P001121, 75D30123C15907, NU38FT000005"
-include_viz: true
-include_ensemble: true
-include_eval: true
 methods: "An ensemble of AR-based time-series models."
 data_inputs: "Daily and weekly incident flu hospitalizations, queried through Delphi Epidata API."
 methods_long: "A basic quantile autoregression fit using lagged values of influenza-related hospitalization counts (normalized by population). The data are smoothed in time and the latter data source is adjusted to remove systematic day-of-week effects. The model is fit jointly across all 50 US states, the District of Columbia, Puerto Rico, and the Virgin Islands, using the most recently available 21 days of training data. Each of the 23 quantiles is learned using a separate quantile regression with nonnegativity and quantile sorting constraints applied post hoc. All data signals are available as indicators through the Delphi Epidata API (https://cmu-delphi.github.io/delphi-epidata)."