{"id":"W2896472034","doi":"10.1016/j.energy.2018.10.047","title":"Performance assessment of photovoltaic modules based on daily energy generation estimation","year":2018,"lang":"en","type":"article","venue":"Energy","topic":"Solar Radiation and Photovoltaics","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"National Natural Science Foundation of China","keywords":"Photovoltaic system; Reliability engineering; Energy (signal processing); Estimation; Energy performance; Environmental science; Computer science; Automotive engineering; Engineering; Efficient energy use; Electrical engineering; Systems engineering; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000171919,0.0001210705,0.0001195849,0.000169368,0.0001348377,0.00005826521,0.0003206718,0.00006255397,0.000047884],"category_scores_gemma":[0.00001832428,0.0001163898,0.00004358086,0.0003455644,0.00004191371,0.000295745,0.00003734163,0.00004325561,0.000006931198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006574401,"about_ca_system_score_gemma":0.0001169545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002056586,"about_ca_topic_score_gemma":0.00006868294,"domain_scores_codex":[0.9989284,0.00007350727,0.0002285826,0.0002666874,0.0003491971,0.0001536484],"domain_scores_gemma":[0.9991145,0.0000447264,0.000144391,0.0004916979,0.0001437859,0.00006093809],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002593053,0.0003885968,0.002785085,0.0000255437,0.00003363693,0.000002956763,0.0002927961,0.3106121,0.2024686,0.2493972,0.006629258,0.2273382],"study_design_scores_gemma":[0.0002153922,0.0002284716,0.004772321,0.000009591659,0.000002429684,8.57603e-7,0.000001086198,0.794569,0.1947118,0.0002109663,0.005176944,0.0001010873],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07856831,0.0000116033,0.9146878,0.0000643533,0.0005015482,0.0000325838,0.000002510813,0.00008039872,0.006050918],"genre_scores_gemma":[0.9393203,0.00001308533,0.05924156,0.0009826192,0.000175763,0.00002224929,0.00003764814,0.000009426165,0.0001973342],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.860752,"threshold_uncertainty_score":0.4746238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01666010049414377,"score_gpt":0.2537490410369478,"score_spread":0.2370889405428041,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}