{"id":"W4398620497","doi":"10.7910/dvn/cvvdqj","title":"administrative data (communes, departements, ...)","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"European and International Law Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Nautical Research Society","funders":"","keywords":"Geography; Genealogy; Demography; History; Sociology","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000788726,0.0002509117,0.0003100387,0.00007148542,0.0004840443,0.0002212048,0.003530184,0.0001386426,0.03187734],"category_scores_gemma":[0.0007027576,0.0002446726,0.00006362963,0.0001060822,0.0003618193,0.0006505549,0.001944765,0.0003548798,0.217266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001139964,"about_ca_system_score_gemma":0.0003829985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003666444,"about_ca_topic_score_gemma":0.01069147,"domain_scores_codex":[0.9976414,0.0003890553,0.0003264325,0.0005653125,0.0007382927,0.0003394557],"domain_scores_gemma":[0.9969856,0.000211577,0.000262108,0.002306398,0.0001193399,0.0001150177],"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":[0.00001733112,0.00008350502,0.00001908802,0.0000264756,0.000179821,0.00003704672,0.0001053712,1.067178e-7,2.438562e-7,0.001725704,0.9977335,0.00007184911],"study_design_scores_gemma":[0.0001991006,0.00003456653,0.00003719697,0.00007381249,0.00009755365,0.000001004508,0.0007912733,0.000002835941,4.465779e-7,0.00001650896,0.9984712,0.0002745218],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000001725226,0.000008815398,0.000003736602,0.00003943045,0.001435248,0.0003203922,0.9342568,0.00003317063,0.06390069],"genre_scores_gemma":[0.00002922914,0.003659167,0.00009731067,0.0006035951,0.0006117443,0.000008671051,0.9854662,0.00001540848,0.009508668],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1853887,"threshold_uncertainty_score":0.9977461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1510303051643572,"score_gpt":0.3827772754534638,"score_spread":0.2317469702891067,"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."}}