{"meta":{"query_hash":"8da048c861fd","filters":{"venue":"IEEE Energy Sustainability Magazine"},"cohort_total":2,"direct_labels_cover":0,"predictions_cover":2,"exported":2,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/8da048c861fd","api":"https://metacan.xera.ac/api/v1/cohort?venue=IEEE+Energy+Sustainability+Magazine"},"results":[{"id":"W4414604338","doi":"10.1109/esm.2025.3583600","title":"Driving Sustainability Through Fleet Electrification, Smart Routing, and Peer-to-Peer Energy Trading: Energy Operations Can Become a Source of Profit","year":2025,"lang":"en","type":"article","venue":"IEEE Energy Sustainability Magazine","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Electrification; Renewable energy; Electricity; Truck; Energy supply; Profit (economics); Backup; Energy storage; Grid; Energy source","score_opus":0.004416581184848552,"score_gpt":0.226274629060021,"score_spread":0.22185804787517244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414604338","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.52404445,0.0006312281,0.4546243,0.015060747,0.0004288992,0.000625101,0.000029856063,0.0006748833,0.0038805518],"genre_scores_gemma":[0.9839158,0.000047472447,0.0007681489,0.0003907772,0.00014528296,0.00022989923,0.00007005904,0.00007546827,0.014357107],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.996449,0.00020385475,0.0010042172,0.0008378926,0.00052269624,0.0009823424],"domain_scores_gemma":[0.9959029,0.00020984832,0.00010060391,0.0009608266,0.0025836418,0.00024220096],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006614119,0.0005547088,0.0007139198,0.00041319395,0.00035250248,0.0001416299,0.0004780739,0.00034159378,0.000034562505],"category_scores_gemma":[0.0011091686,0.00057904905,0.00016972514,0.001909352,0.0002136718,0.00033562622,0.00008523231,0.00035537174,3.0268873e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017830457,0.00042594818,0.032192662,0.0014111125,0.0006351541,0.000022225937,0.0048253615,0.36122867,0.03954901,0.4250648,0.038393322,0.09607342],"study_design_scores_gemma":[0.0020391927,0.0006258591,0.024217416,0.00011274217,0.00027764466,0.000042331787,0.0020033289,0.29744235,0.19800074,0.098072,0.3751337,0.002032693],"about_ca_topic_score_codex":0.0037238265,"about_ca_topic_score_gemma":0.002632372,"teacher_disagreement_score":0.45987135,"about_ca_system_score_codex":0.0015184359,"about_ca_system_score_gemma":0.00075019745,"threshold_uncertainty_score":0.9996661},"labels":[],"label_agreement":null},{"id":"W4415934845","doi":"10.1109/esm.2025.3606669","title":"Leveraging Artificial Intelligence for Enhancing Power Grid Resilience to Extreme Weather Events: Applications and Challenges","year":2025,"lang":"","type":"article","venue":"IEEE Energy Sustainability Magazine","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Resilience (materials science); Extreme weather; Adaptation (eye); Electric power system; Duration (music); Grid; Electric power; Psychological resilience","score_opus":0.02115340527420706,"score_gpt":0.26824119589912654,"score_spread":0.24708779062491948,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415934845","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013952018,0.0058285925,0.9675256,0.008090134,0.0013357204,0.0019151439,0.000095476455,0.00025111125,0.0010062325],"genre_scores_gemma":[0.99342,0.00094209233,0.002586005,0.00013721597,0.0003573133,0.001366295,0.000027409322,0.000070806476,0.00109286],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9957867,0.00013544719,0.0011685704,0.0014201126,0.0003253197,0.0011638437],"domain_scores_gemma":[0.99688464,0.0005288473,0.00012049163,0.0010956777,0.0010545119,0.0003158206],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0011389046,0.00064825104,0.00063279597,0.00042878313,0.00042145193,0.00014264236,0.00051872694,0.00031299997,0.00005380704],"category_scores_gemma":[0.00093561003,0.00079173193,0.00019248681,0.001046594,0.0002155902,0.0004107374,0.00024880655,0.00032144788,0.000020250483],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006275762,0.0009554395,0.00015745465,0.004495967,0.00028261193,0.000011893134,0.002563445,0.25577417,0.012973724,0.22058237,0.0010921042,0.5004833],"study_design_scores_gemma":[0.0009184828,0.0011828251,0.003947025,0.0010810605,0.00046849632,0.00001638259,0.017569728,0.11264918,0.06761998,0.27943614,0.5116549,0.0034558023],"about_ca_topic_score_codex":0.00007294502,"about_ca_topic_score_gemma":0.0004055644,"teacher_disagreement_score":0.979468,"about_ca_system_score_codex":0.0017743416,"about_ca_system_score_gemma":0.0003719118,"threshold_uncertainty_score":0.99945337},"labels":[],"label_agreement":null}]}