{"id":"W4415242843","doi":"10.4000/14yx6","title":"L’ODDyssée du climat et des migrations","year":2025,"lang":"fr","type":"article","venue":"Mondes & Migrations","topic":"Climate Change, Adaptation, Migration","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Musée de la Civilisation","funders":"","keywords":"Ethnic group; Rural population; Field (mathematics)","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":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009764113,0.000419548,0.0003763569,0.0004656946,0.002849156,0.0006360348,0.0004239274,0.0003881079,0.001143038],"category_scores_gemma":[0.0009617269,0.0004870093,0.0003133753,0.002656016,0.001319668,0.001671543,0.00009591554,0.0003469531,0.0006014394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009596928,"about_ca_system_score_gemma":0.0008384135,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01533752,"about_ca_topic_score_gemma":0.4915793,"domain_scores_codex":[0.9965196,0.0007670908,0.0008233764,0.0006184213,0.0005188406,0.0007526601],"domain_scores_gemma":[0.9973719,0.0008403073,0.0002747596,0.0005047563,0.0007804061,0.0002278938],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001533381,0.0007026014,0.02039785,0.000123359,0.0001428296,0.000005728723,0.1158487,0.00119524,0.001350155,0.5442716,0.3020437,0.01390287],"study_design_scores_gemma":[0.0006041006,0.0001053464,0.04271064,0.0004382724,0.0004752377,0.000006288619,0.04935117,0.007611549,0.00044085,0.05601912,0.8415658,0.0006715981],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4810478,0.05945135,0.04948916,0.2895557,0.00570521,0.00239251,0.001027592,0.0008442083,0.1104864],"genre_scores_gemma":[0.8121338,0.01539682,0.007570947,0.003159428,0.0007255389,0.0004473002,0.0007711151,0.00005982953,0.1597352],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5395221,"threshold_uncertainty_score":0.99977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1134622440282161,"score_gpt":0.3527957813532593,"score_spread":0.2393335373250432,"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."}}