{"id":"W2112478781","doi":"10.7202/1011543ar","title":"Recourir aux microsimulations pour étudier la mortalité de crise : illustration par la mortalité au Burundi en 1993","year":2012,"lang":"fr","type":"article","venue":"Cahiers québécois de démographie","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Political science; Humanities; Geography; Art","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.008772502,0.0007638999,0.0007727703,0.001373169,0.001317174,0.0005722927,0.000878098,0.001380949,0.0002968259],"category_scores_gemma":[0.002094223,0.0007812454,0.0009852345,0.003250713,0.001959305,0.001485003,0.0001019372,0.001198848,0.0002055325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004797487,"about_ca_system_score_gemma":0.001817315,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0228783,"about_ca_topic_score_gemma":0.01382984,"domain_scores_codex":[0.9918575,0.002216395,0.001657669,0.001041551,0.001298469,0.001928439],"domain_scores_gemma":[0.9930664,0.003245082,0.0007110451,0.001187481,0.0006097567,0.001180227],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001544495,0.001456738,0.7507333,0.0001938071,0.0008962672,0.0001392352,0.04981215,0.008697213,0.002213138,0.08337177,0.02487773,0.07745421],"study_design_scores_gemma":[0.002504149,0.0002411978,0.5463236,0.0005038084,0.002033313,0.0005058942,0.03332812,0.02897249,0.000472472,0.06572163,0.3169519,0.002441446],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.939655,0.01757454,0.02577783,0.004067073,0.001945814,0.000534226,0.0002780032,0.0002256919,0.009941814],"genre_scores_gemma":[0.9829293,0.004889945,0.004997683,0.0009323104,0.0009662074,0.0001286739,0.0001204139,0.0001174048,0.004918059],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2920741,"threshold_uncertainty_score":0.999983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.058592651338567,"score_gpt":0.3503350643905342,"score_spread":0.2917424130519672,"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."}}