[{"run_id":"20260906T231458-5fdd2fff","observed_at":"2026-09-06 23:14:58.172943+00:00","course_uid":"course_62e24e3815f7c34ae632f724","course_id":"ATMOCN/GEOSCI 353","catalog_version_id":"b70e0f885711a6536f59325795d56f55b5607804b02e8fea704d8a8fcc8e8f9e","record_version_id":"3985f520fef441a2144f5bdaaa1fb8c905ba6ab09a2b52238711c9e6ba761855","job_id":"enrich-5291a20b802b9bbbe22b24cb","output_id":"5ac99c3cca05a1724e3bab99235482655b1522e63e2090657a871caf976f634d","section":"requirements","status":"invalid","value_json":null,"candidate_json":"{\"nodes\":[{\"children\":[\"n0\",\"n1\"],\"condition\":null,\"course\":null,\"evidence\":\"MATH 222or graduate/professional standing\",\"id\":\"n0\",\"kind\":\"any\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":222,\"minimum_grade\":null,\"subjects\":[\"MATH\"],\"timing\":\"prior\"},\"evidence\":\"MATH 222\",\"id\":\"n1\",\"kind\":\"course\"},{\"children\":[],\"condition\":\"graduate/professional standing\",\"course\":null,\"evidence\":\"graduate/professional standing\",\"id\":\"n2\",\"kind\":\"condition\"}],\"notes\":[],\"root\":\"n0\",\"status\":\"parsed\"}","error":"Node n0 references itself; remove the self-reference.\nCycle reaches node n0; requirement graphs must be trees.\nUnreachable nodes: n2; connect all conditions and exclusions to the root.","model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":false},{"run_id":"20260906T231458-5fdd2fff","observed_at":"2026-09-06 23:14:58.172943+00:00","course_uid":"course_62e24e3815f7c34ae632f724","course_id":"ATMOCN/GEOSCI 353","catalog_version_id":"b70e0f885711a6536f59325795d56f55b5607804b02e8fea704d8a8fcc8e8f9e","record_version_id":"3985f520fef441a2144f5bdaaa1fb8c905ba6ab09a2b52238711c9e6ba761855","job_id":"enrich-5291a20b802b9bbbe22b24cb","output_id":"5ac99c3cca05a1724e3bab99235482655b1522e63e2090657a871caf976f634d","section":"search_profile","status":"valid","value_json":"{\"assumed_background\":[{\"evidence\":[{\"course_id\":\"MATH 222\",\"field\":\"description\",\"quote\":\"Techniques of integration, improper integrals, first order ordinary differential equations, sequences and series, Taylor series, vector geometry in two and three dimensions.\"}],\"text\":\"Calculus and analytic geometry\"}],\"search_phrases\":[\"geoscience programming python\",\"numerical computing earth sciences\",\"machine learning geoscience\",\"geospatial data visualization python\"],\"skills_taught\":[{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"Introduction to scientific programming with a focus on geoscience applications, utilizing Python as the primary programming language.\"}],\"text\":\"Scientific programming in Python\"},{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"analytical model implementation, time series analysis, and geospatial data visualization.\"}],\"text\":\"Analytical model implementation and time series analysis\"},{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"elementary topics in numerical computing and machine learning.\"}],\"text\":\"Numerical computing and machine learning\"}],\"summary\":{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"title\",\"quote\":\"PROGRAMMING FOR EARTH SCIENTISTS\"},{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"Introduction to scientific programming with a focus on geoscience applications, utilizing Python as the primary programming language.\"}],\"text\":\"Programming for Earth Scientists introduces scientific programming in Python for geoscience applications, covering numerical computing, machine learning, and data visualization.\"},\"topics\":[{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"geoscience applications\"}],\"text\":\"Geoscience applications\"},{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"time series analysis\"}],\"text\":\"Time series analysis\"},{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"geospatial data visualization\"}],\"text\":\"Geospatial data visualization\"},{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"numerical computing and machine learning\"}],\"text\":\"Numerical computing and machine learning\"}]}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":false},{"run_id":"20260906T231458-5fdd2fff","observed_at":"2026-09-06 23:14:58.172943+00:00","course_uid":"course_62e24e3815f7c34ae632f724","course_id":"ATMOCN/GEOSCI 353","catalog_version_id":"b70e0f885711a6536f59325795d56f55b5607804b02e8fea704d8a8fcc8e8f9e","record_version_id":"3985f520fef441a2144f5bdaaa1fb8c905ba6ab09a2b52238711c9e6ba761855","job_id":"enrich-5291a20b802b9bbbe22b24cb","output_id":"5ac99c3cca05a1724e3bab99235482655b1522e63e2090657a871caf976f634d","section":"student_experience","status":"insufficient_evidence","value_json":"{\"status\":\"insufficient_evidence\",\"themes\":[]}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":false},{"run_id":"20260907T155543-ce3781c4","observed_at":"2026-09-07 15:55:43.033547+00:00","course_uid":"course_62e24e3815f7c34ae632f724","course_id":"ATMOCN/GEOSCI 353","catalog_version_id":"b70e0f885711a6536f59325795d56f55b5607804b02e8fea704d8a8fcc8e8f9e","record_version_id":"3985f520fef441a2144f5bdaaa1fb8c905ba6ab09a2b52238711c9e6ba761855","job_id":"enrich-5590a4969e0a630fe46a86e8","output_id":"dea9667f789383ddf4433f05fb002b0f4a6a1e11c1fb5e196c4f2f6d82d552d9","section":"requirements","status":"valid","value_json":"{\"nodes\":[{\"children\":[\"n1\",\"n2\"],\"condition\":null,\"course\":null,\"evidence\":\"MATH 222or graduate/professional standing\",\"id\":\"n0\",\"kind\":\"any\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":222,\"minimum_grade\":null,\"subjects\":[\"MATH\"],\"timing\":\"prior\"},\"evidence\":\"MATH 222\",\"id\":\"n1\",\"kind\":\"course\"},{\"children\":[],\"condition\":\"graduate/professional standing\",\"course\":null,\"evidence\":\"graduate/professional standing\",\"id\":\"n2\",\"kind\":\"condition\"}],\"notes\":[],\"root\":\"n0\",\"status\":\"parsed\"}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":true},{"run_id":"20260907T155543-ce3781c4","observed_at":"2026-09-07 15:55:43.033547+00:00","course_uid":"course_62e24e3815f7c34ae632f724","course_id":"ATMOCN/GEOSCI 353","catalog_version_id":"b70e0f885711a6536f59325795d56f55b5607804b02e8fea704d8a8fcc8e8f9e","record_version_id":"3985f520fef441a2144f5bdaaa1fb8c905ba6ab09a2b52238711c9e6ba761855","job_id":"enrich-5590a4969e0a630fe46a86e8","output_id":"dea9667f789383ddf4433f05fb002b0f4a6a1e11c1fb5e196c4f2f6d82d552d9","section":"search_profile","status":"valid","value_json":"{\"assumed_background\":[{\"evidence\":[{\"course_id\":\"MATH 222\",\"field\":\"description\",\"quote\":\"Techniques of integration, improper integrals, first order ordinary differential equations, sequences and series, Taylor series, vector geometry in two and three dimensions.\"}],\"text\":\"Calculus and analytic geometry\"}],\"search_phrases\":[\"geoscience programming python\",\"numerical computing earth sciences\",\"machine learning geoscience\",\"geospatial data visualization python\"],\"skills_taught\":[{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"Introduction to scientific programming with a focus on geoscience applications, utilizing Python as the primary programming language.\"}],\"text\":\"Scientific programming in Python\"},{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"analytical model implementation, time series analysis, and geospatial data visualization.\"}],\"text\":\"Analytical model implementation and time series analysis\"},{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"elementary topics in numerical computing and machine learning.\"}],\"text\":\"Numerical computing and machine learning\"}],\"summary\":{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"title\",\"quote\":\"PROGRAMMING FOR EARTH SCIENTISTS\"},{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"Introduction to scientific programming with a focus on geoscience applications, utilizing Python as the primary programming language.\"}],\"text\":\"Programming for Earth Scientists introduces scientific programming in Python for geoscience applications, covering numerical computing, machine learning, and data visualization.\"},\"topics\":[{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"geoscience applications\"}],\"text\":\"Geoscience applications\"},{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"time series analysis\"}],\"text\":\"Time series analysis\"},{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"geospatial data visualization\"}],\"text\":\"Geospatial data visualization\"},{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"numerical computing and machine learning\"}],\"text\":\"Numerical computing and machine learning\"}]}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":true},{"run_id":"20260907T155543-ce3781c4","observed_at":"2026-09-07 15:55:43.033547+00:00","course_uid":"course_62e24e3815f7c34ae632f724","course_id":"ATMOCN/GEOSCI 353","catalog_version_id":"b70e0f885711a6536f59325795d56f55b5607804b02e8fea704d8a8fcc8e8f9e","record_version_id":"3985f520fef441a2144f5bdaaa1fb8c905ba6ab09a2b52238711c9e6ba761855","job_id":"enrich-5590a4969e0a630fe46a86e8","output_id":"dea9667f789383ddf4433f05fb002b0f4a6a1e11c1fb5e196c4f2f6d82d552d9","section":"student_experience","status":"insufficient_evidence","value_json":"{\"status\":\"insufficient_evidence\",\"themes\":[]}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":true},{"run_id":"20260906T231458-5fdd2fff","observed_at":"2026-09-06 23:14:58.172943+00:00","course_uid":"course_62e24e3815f7c34ae632f724","course_id":"ATMOCN/GEOSCI 353","catalog_version_id":"b70e0f885711a6536f59325795d56f55b5607804b02e8fea704d8a8fcc8e8f9e","record_version_id":"3985f520fef441a2144f5bdaaa1fb8c905ba6ab09a2b52238711c9e6ba761855","job_id":"enrich-789789da373eecc1ff75f626","output_id":"b7255d7b839399083b3228371fb33ff5c4849df8f2c63ad32953c4d32a05f6a6","section":"requirements","status":"valid","value_json":"{\"nodes\":[{\"children\":[\"n1\",\"n2\"],\"condition\":null,\"course\":null,\"evidence\":\"MATH 222or graduate/professional standing\",\"id\":\"n0\",\"kind\":\"any\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":222,\"minimum_grade\":null,\"subjects\":[\"MATH\"],\"timing\":\"prior\"},\"evidence\":\"MATH 222\",\"id\":\"n1\",\"kind\":\"course\"},{\"children\":[],\"condition\":\"graduate/professional standing\",\"course\":null,\"evidence\":\"graduate/professional standing\",\"id\":\"n2\",\"kind\":\"condition\"}],\"notes\":[],\"root\":\"n0\",\"status\":\"parsed\"}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":false},{"run_id":"20260906T231458-5fdd2fff","observed_at":"2026-09-06 23:14:58.172943+00:00","course_uid":"course_62e24e3815f7c34ae632f724","course_id":"ATMOCN/GEOSCI 353","catalog_version_id":"b70e0f885711a6536f59325795d56f55b5607804b02e8fea704d8a8fcc8e8f9e","record_version_id":"3985f520fef441a2144f5bdaaa1fb8c905ba6ab09a2b52238711c9e6ba761855","job_id":"enrich-789789da373eecc1ff75f626","output_id":"b7255d7b839399083b3228371fb33ff5c4849df8f2c63ad32953c4d32a05f6a6","section":"search_profile","status":"valid","value_json":"{\"assumed_background\":[{\"evidence\":[{\"course_id\":\"MATH 222\",\"field\":\"description\",\"quote\":\"Techniques of integration, improper integrals, first order ordinary differential equations, sequences and series, Taylor series, vector geometry in two and three dimensions.\"}],\"text\":\"Calculus and analytic geometry\"}],\"search_phrases\":[\"geoscience programming python\",\"numerical computing earth sciences\",\"machine learning geoscience\",\"geospatial data visualization python\"],\"skills_taught\":[{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"Introduction to scientific programming with a focus on geoscience applications, utilizing Python as the primary programming language.\"}],\"text\":\"Scientific programming in Python\"},{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"analytical model implementation, time series analysis, and geospatial data visualization.\"}],\"text\":\"Analytical model implementation and time series analysis\"},{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"elementary topics in numerical computing and machine learning.\"}],\"text\":\"Numerical computing and machine learning\"}],\"summary\":{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"title\",\"quote\":\"PROGRAMMING FOR EARTH SCIENTISTS\"},{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"Introduction to scientific programming with a focus on geoscience applications, utilizing Python as the primary programming language.\"}],\"text\":\"Programming for Earth Scientists introduces scientific programming in Python for geoscience applications, covering numerical computing, machine learning, and data visualization.\"},\"topics\":[{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"geoscience applications\"}],\"text\":\"Geoscience applications\"},{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"time series analysis\"}],\"text\":\"Time series analysis\"},{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"geospatial data visualization\"}],\"text\":\"Geospatial data visualization\"},{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"numerical computing and machine learning\"}],\"text\":\"Numerical computing and machine learning\"}]}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":false},{"run_id":"20260906T231458-5fdd2fff","observed_at":"2026-09-06 23:14:58.172943+00:00","course_uid":"course_62e24e3815f7c34ae632f724","course_id":"ATMOCN/GEOSCI 353","catalog_version_id":"b70e0f885711a6536f59325795d56f55b5607804b02e8fea704d8a8fcc8e8f9e","record_version_id":"3985f520fef441a2144f5bdaaa1fb8c905ba6ab09a2b52238711c9e6ba761855","job_id":"enrich-789789da373eecc1ff75f626","output_id":"b7255d7b839399083b3228371fb33ff5c4849df8f2c63ad32953c4d32a05f6a6","section":"student_experience","status":"insufficient_evidence","value_json":"{\"status\":\"insufficient_evidence\",\"themes\":[]}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":false},{"run_id":"20260907T155543-ce3781c4","observed_at":"2026-09-07 15:55:43.033547+00:00","course_uid":"course_62e24e3815f7c34ae632f724","course_id":"ATMOCN/GEOSCI 353","catalog_version_id":"b70e0f885711a6536f59325795d56f55b5607804b02e8fea704d8a8fcc8e8f9e","record_version_id":"3985f520fef441a2144f5bdaaa1fb8c905ba6ab09a2b52238711c9e6ba761855","job_id":"enrich-8b774950c2b6adfdc46d1b82","output_id":"002f6fb7d8b9635843fb07c4dc390015d2d8cfee4b0d2b13ab2ef4ec90db2813","section":"requirements","status":"valid","value_json":"{\"nodes\":[{\"children\":[\"n1\",\"n2\"],\"condition\":null,\"course\":null,\"evidence\":\"MATH 222or graduate/professional standing\",\"id\":\"n0\",\"kind\":\"any\"},{\"children\":[],\"condition\":null,\"course\":{\"course_number\":222,\"minimum_grade\":null,\"subjects\":[\"MATH\"],\"timing\":\"prior\"},\"evidence\":\"MATH 222\",\"id\":\"n1\",\"kind\":\"course\"},{\"children\":[],\"condition\":\"graduate/professional standing\",\"course\":null,\"evidence\":\"graduate/professional standing\",\"id\":\"n2\",\"kind\":\"condition\"}],\"notes\":[],\"root\":\"n0\",\"status\":\"parsed\"}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":true},{"run_id":"20260907T155543-ce3781c4","observed_at":"2026-09-07 15:55:43.033547+00:00","course_uid":"course_62e24e3815f7c34ae632f724","course_id":"ATMOCN/GEOSCI 353","catalog_version_id":"b70e0f885711a6536f59325795d56f55b5607804b02e8fea704d8a8fcc8e8f9e","record_version_id":"3985f520fef441a2144f5bdaaa1fb8c905ba6ab09a2b52238711c9e6ba761855","job_id":"enrich-8b774950c2b6adfdc46d1b82","output_id":"002f6fb7d8b9635843fb07c4dc390015d2d8cfee4b0d2b13ab2ef4ec90db2813","section":"search_profile","status":"valid","value_json":"{\"assumed_background\":[{\"evidence\":[{\"course_id\":\"MATH 222\",\"field\":\"description\",\"quote\":\"Techniques of integration, improper integrals, first order ordinary differential equations, sequences and series, Taylor series, vector geometry in two and three dimensions.\"}],\"text\":\"Calculus and analytic geometry\"}],\"search_phrases\":[\"geoscience programming python\",\"numerical computing earth sciences\",\"machine learning geoscience\",\"geospatial data visualization python\"],\"skills_taught\":[{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"Introduction to scientific programming with a focus on geoscience applications, utilizing Python as the primary programming language.\"}],\"text\":\"Scientific programming in Python\"},{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"analytical model implementation, time series analysis, and geospatial data visualization.\"}],\"text\":\"Analytical model implementation and time series analysis\"},{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"elementary topics in numerical computing and machine learning.\"}],\"text\":\"Numerical computing and machine learning\"}],\"summary\":{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"title\",\"quote\":\"PROGRAMMING FOR EARTH SCIENTISTS\"},{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"Introduction to scientific programming with a focus on geoscience applications, utilizing Python as the primary programming language.\"}],\"text\":\"Programming for Earth Scientists introduces scientific programming in Python for geoscience applications, covering numerical computing, machine learning, and data visualization.\"},\"topics\":[{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"geoscience applications\"}],\"text\":\"Geoscience applications\"},{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"time series analysis\"}],\"text\":\"Time series analysis\"},{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"geospatial data visualization\"}],\"text\":\"Geospatial data visualization\"},{\"evidence\":[{\"course_id\":\"ATMOCN/GEOSCI 353\",\"field\":\"description\",\"quote\":\"numerical computing and machine learning\"}],\"text\":\"Numerical computing and machine learning\"}]}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":true},{"run_id":"20260907T155543-ce3781c4","observed_at":"2026-09-07 15:55:43.033547+00:00","course_uid":"course_62e24e3815f7c34ae632f724","course_id":"ATMOCN/GEOSCI 353","catalog_version_id":"b70e0f885711a6536f59325795d56f55b5607804b02e8fea704d8a8fcc8e8f9e","record_version_id":"3985f520fef441a2144f5bdaaa1fb8c905ba6ab09a2b52238711c9e6ba761855","job_id":"enrich-8b774950c2b6adfdc46d1b82","output_id":"002f6fb7d8b9635843fb07c4dc390015d2d8cfee4b0d2b13ab2ef4ec90db2813","section":"student_experience","status":"insufficient_evidence","value_json":"{\"status\":\"insufficient_evidence\",\"themes\":[]}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":true},{"run_id":"20260907T155543-ce3781c4","observed_at":"2026-09-07 15:55:43.033547+00:00","course_uid":"course_62e24e3815f7c34ae632f724","course_id":"ATMOCN/GEOSCI 353","catalog_version_id":"b70e0f885711a6536f59325795d56f55b5607804b02e8fea704d8a8fcc8e8f9e","record_version_id":"3985f520fef441a2144f5bdaaa1fb8c905ba6ab09a2b52238711c9e6ba761855","job_id":"enrich-8b774950c2b6adfdc46d1b82","output_id":"002f6fb7d8b9635843fb07c4dc390015d2d8cfee4b0d2b13ab2ef4ec90db2813","section":"student_summary","status":"valid","value_json":"{\"context_hash\":\"6c748e118f76852d520eb0bda4166df7f849ccb8b9cbe9d0f121805065c925af\",\"course_id\":\"ATMOCN/GEOSCI 353\",\"current_instructors\":[],\"difficulty_workload\":[],\"errors\":[],\"historical_context\":[],\"message\":\"No course-specific reviews available\",\"offered\":false,\"profile_hash\":\"672f506f2fc2f46a071b9777f4a92cc197b2ccdeef25590e9285146d8c7e7f90\",\"quick_take\":[],\"student_experience\":[],\"task_hash\":\"74fb0997943e888960bbc9e47db8c4fd12e4292d55c20509d8d89db6a9910f68\",\"teaching_history\":[],\"term_id\":\"1272\",\"term_name\":\"2026 Fall\",\"version\":2}","candidate_json":null,"error":null,"model":"nvidia/Qwen3.6-35B-A3B-NVFP4","model_revision":"1355db6a052410cfd62085d94b58866fd0f2c3c5","selected_for_release":true}]