{"id":"W2286864653","doi":"","title":"L’échantillon démographique permanent (EDP) de l’INSEE (France).","year":2013,"lang":"fr","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Multiculturalism, Politics, Migration, Gender","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Political science; Philosophy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016172,0.0009055146,0.0008655039,0.005904678,0.001494471,0.002643388,0.0007580651,0.0007557267,0.05285133],"category_scores_gemma":[0.003447693,0.0003848596,0.0008419593,0.009539126,0.0006199208,0.001384309,0.001076687,0.002027008,0.005725975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01385535,"about_ca_system_score_gemma":0.009268289,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.8492957,"about_ca_topic_score_gemma":0.7779142,"domain_scores_codex":[0.9988903,0.0002835534,0.00006291911,0.0002027926,0.0003225478,0.000237887],"domain_scores_gemma":[0.9980024,0.0004085533,0.0001494927,0.0002538099,0.001011989,0.0001737589],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0004395518,0.0001272045,0.03231141,0.0006369626,0.0002354935,0.0002463573,0.001392615,0.002938383,0.0006567001,0.06568512,0.6410876,0.2542426],"study_design_scores_gemma":[0.000031746,0.00002568428,0.1359694,0.0002117578,0.00001925136,0.0001077766,0.0004711434,0.0005616631,0.0003601087,0.001381679,0.8608252,0.00003459572],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.06766497,0.06029969,0.01341506,0.01552939,0.003671652,0.0003315411,0.5177855,0.002370857,0.3189313],"genre_scores_gemma":[0.309985,0.02612933,0.0225787,0.001301583,0.001031299,0.001077398,0.180891,0.0009900606,0.4560156],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8492957,"threshold_uncertainty_score":0.3031837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0960781196469708,"score_gpt":0.3965589927599311,"score_spread":0.3004808731129603,"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."}}