{"id":"W7132101978","doi":"","title":"DEI at Schneider Electric: From \"Why\" to \"How\"","year":2023,"lang":"","type":"other","venue":"CEIBS Institutional Repository","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Casa","funders":"","keywords":"Set (abstract data type); Perspective (graphical); Context (archaeology); Subject (documents)","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":["metaepi_narrow","sts","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.0007355292,0.002656407,0.002103768,0.002632997,0.003774808,0.0008508714,0.002505899,0.002759072,0.006162963],"category_scores_gemma":[0.002157761,0.002969463,0.001298726,0.003489504,0.001617935,0.0008112792,0.001793665,0.002246053,0.2239915],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.01664677,"about_ca_system_score_gemma":0.005911154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002549791,"about_ca_topic_score_gemma":0.002518841,"domain_scores_codex":[0.9853554,0.0006781784,0.001957308,0.004717398,0.004688296,0.002603447],"domain_scores_gemma":[0.9913256,0.0008367574,0.001486018,0.003281807,0.0009756631,0.002094197],"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":[0.0009077755,0.0006287208,0.002655602,0.0001461351,0.00269003,0.005113289,0.0002724844,0.001631009,0.1717383,0.00843969,0.8043576,0.001419365],"study_design_scores_gemma":[0.001517726,0.0002157466,0.0115232,0.002079402,0.0008128257,0.0006905166,0.00004539208,0.0002670008,0.02298977,0.000307831,0.9564632,0.003087357],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.03353293,0.0144556,0.001364827,0.001024708,0.03543504,0.004272286,0.003256846,0.004897353,0.9017604],"genre_scores_gemma":[0.1111962,0.0003841914,0.001902959,0.00137665,0.01539034,0.0009626679,0.0008567742,0.005681138,0.8622491],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2178286,"threshold_uncertainty_score":0.9997244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01804165026566779,"score_gpt":0.2433041841965044,"score_spread":0.2252625339308366,"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."}}