{"id":"W3047166786","doi":"","title":"Migrations vers les campagnes et gentrification rurale","year":2018,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"French Urban and Social Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"GDG Environnement","funders":"","keywords":"Gentrification; Geography; Computer science; Economics; Economic growth","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009780299,0.0005102779,0.0004671729,0.001325353,0.005598185,0.003340558,0.000526227,0.001388583,0.01500998],"category_scores_gemma":[0.001851041,0.0001967232,0.0003417992,0.002388642,0.005269963,0.001667554,0.00233131,0.00294573,0.0007064383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006513399,"about_ca_system_score_gemma":0.003355689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2037883,"about_ca_topic_score_gemma":0.2327526,"domain_scores_codex":[0.9990262,0.0004306866,0.00001300858,0.00008004587,0.00007883946,0.0003713004],"domain_scores_gemma":[0.9993287,0.000236382,0.00009859676,0.00003983084,0.00008025497,0.000216097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0005359571,0.0002024917,0.02666317,0.0003012148,0.0000996404,0.002723525,0.1089831,0.001236339,0.00300773,0.7695944,0.01162402,0.07502846],"study_design_scores_gemma":[0.0002584683,0.0002853967,0.1855238,0.0004173296,0.00005563646,0.002143942,0.107209,0.0007630913,0.0008103411,0.04669208,0.6557311,0.0001097157],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8924911,0.006007676,0.000718343,0.01504327,0.0002844923,0.00001602778,0.0002223755,0.00003454942,0.08518212],"genre_scores_gemma":[0.9542475,0.0028387,0.000276206,0.0005068907,0.0002400314,0.00001483301,0.00005544883,0.00001974613,0.04180057],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2037883,"threshold_uncertainty_score":0.4052042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03528030905702875,"score_gpt":0.2576503342587108,"score_spread":0.2223700252016821,"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."}}