{"id":"W4394423949","doi":"10.6084/m9.figshare.13206008","title":"wind_data.txt","year":2020,"lang":"en","type":"dataset","venue":"Figshare","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Meteorology; Environmental science; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000008907759,0.0002544739,0.0002140631,0.00005188142,0.00003400525,0.0000647302,0.0004035506,0.0002525935,0.3515752],"category_scores_gemma":[0.0002247114,0.0002648427,0.00007707255,0.0001280747,0.000001779569,0.00007417436,0.000134489,0.0004633367,0.07162909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002318309,"about_ca_system_score_gemma":0.00002382548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004095428,"about_ca_topic_score_gemma":0.0000150583,"domain_scores_codex":[0.9992625,0.000007502472,0.0001613944,0.0001954054,0.0001399836,0.0002332339],"domain_scores_gemma":[0.9994431,0.00004942136,0.00003406329,0.0003351899,0.00001537489,0.0001228246],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[5.48715e-7,0.000002074494,2.069466e-8,0.0006650367,0.00002529486,0.00006510486,0.000004444024,0.0005082684,7.801872e-7,1.902159e-7,0.998234,0.0004942222],"study_design_scores_gemma":[0.00005265145,0.000009525177,0.00000116829,0.001462165,0.00001090205,0.000007201967,0.000001127863,0.0003157323,0.00003713216,0.00000159959,0.9978027,0.0002980704],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[4.021355e-8,0.0002263729,2.350432e-7,0.000004450369,0.0002995483,0.00005493802,0.9971064,0.0003023087,0.002005691],"genre_scores_gemma":[0.000002073302,0.00002505712,0.0000208028,0.000198151,0.0008932161,0.00005151532,0.9987279,0.00004247555,0.00003882856],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2799461,"threshold_uncertainty_score":0.9999804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03011618957374279,"score_gpt":0.2174357169141386,"score_spread":0.1873195273403958,"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."}}