{"id":"W6892721638","doi":"10.5281/zenodo.12573103","title":"CIRAIG/Regioinvent: v1.0.1","year":2024,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coal; Production (economics); Consumption (sociology); Electricity; Energy consumption; Electricity generation","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","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002636265,0.0003034616,0.0002459135,0.0006144329,0.0005985154,0.001343214,0.003282404,0.0001864955,0.009637028],"category_scores_gemma":[0.0001138259,0.0003120029,0.0001211559,0.001178723,0.0001693825,0.0002317159,0.003262856,0.0006093928,0.07386594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001003576,"about_ca_system_score_gemma":0.000003238057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008892152,"about_ca_topic_score_gemma":5.171856e-7,"domain_scores_codex":[0.9975564,0.0002162075,0.0002476949,0.0009542048,0.0004990826,0.0005263842],"domain_scores_gemma":[0.9982091,0.00001403478,0.0001625312,0.00123606,0.0001490287,0.0002292336],"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":[0.000002777633,0.00002788637,3.263448e-8,0.00008827217,0.00004253583,0.00007047368,0.0001376724,0.00001090586,0.00003274976,0.03459685,0.8964401,0.06854969],"study_design_scores_gemma":[0.0001601185,0.00009317016,0.000001843296,0.0001917145,0.00001250637,0.0001469453,0.00001172511,0.0008490095,0.00001558045,0.003714322,0.9944821,0.0003209833],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000001074674,0.001632181,0.0771116,0.001070979,0.0006456815,0.000438395,0.00011468,0.005601445,0.913384],"genre_scores_gemma":[0.001289887,0.001061043,0.006186497,0.0009360914,0.001299145,1.314242e-7,0.001410216,0.02669227,0.9611247],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.09804193,"threshold_uncertainty_score":0.9999332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03245608995530128,"score_gpt":0.2483898152580734,"score_spread":0.2159337253027721,"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."}}