{"id":"W2943555463","doi":"","title":"Gender in the transition to sustainable energy for all: From evidence to inclusive policies","year":2019,"lang":"en","type":"article","venue":"IIASA PURE (International Institute of Applied Systems Analysis)","topic":"Energy and Environment Impacts","field":"Environmental Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"FP7 International Cooperation; Deutsche Gesellschaft für Internationale Zusammenarbeit; Department for International Development; University of Cape Town; University of Twente; Government of the United Kingdom; Multiple Sclerosis Scientific Research Foundation","keywords":"Transition (genetics); Energy transition; Business; Political science; Economic growth; Economics; Medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004739955,0.0001603677,0.0002776217,0.000225145,0.00006850967,0.00006130186,0.0006100341,0.00007533178,0.0002092014],"category_scores_gemma":[0.00002862019,0.0001260973,0.0001269334,0.0005663703,0.00004346382,0.0003475721,0.0001484306,0.00005991014,0.00007271835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000348502,"about_ca_system_score_gemma":0.00001728455,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.014658,"about_ca_topic_score_gemma":0.002897084,"domain_scores_codex":[0.9983498,0.00002877759,0.000369786,0.0003666064,0.0006179804,0.0002669804],"domain_scores_gemma":[0.999323,0.0001071324,0.0001251961,0.0003335587,0.0000219164,0.00008921742],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001153125,0.00006313934,0.0008040642,0.00001079535,0.0002616568,0.000003720754,0.004137757,0.9443519,0.00983387,0.03922309,0.001081089,0.000113579],"study_design_scores_gemma":[0.002726613,0.0004454404,0.1894996,0.00028706,0.001391615,0.00001008825,0.02222783,0.04514777,0.00700578,0.01657452,0.712822,0.001861643],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9468889,0.00004160038,0.03308539,0.002079184,0.0002384142,0.0006879169,0.00005011944,0.00001311469,0.01691536],"genre_scores_gemma":[0.9965875,0.00001611769,0.0003925946,0.001892458,0.00009998985,0.0001878047,0.0001004812,0.00000944138,0.0007136844],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8992041,"threshold_uncertainty_score":0.9919035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01675586766488641,"score_gpt":0.2622662275352673,"score_spread":0.2455103598703809,"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."}}