{"id":"W4408346467","doi":"10.4000/13gk4","title":"Adaptation au climat de variétés de mil et de sorgho dans le Nord-Est du Sénégal : croisement des paramètres pluviométriques, thermiques et phénologiques","year":2025,"lang":"fr","type":"article","venue":"Physio-Géo","topic":"Agriculture and Rural Development Research","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"ASTER","funders":"","keywords":"Physics; Forestry; Humanities; Art; Geography","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":[],"consensus_categories":[],"category_scores_codex":[0.00110289,0.0004232775,0.0003873663,0.00004765645,0.0008414598,0.0003228597,0.0006101137,0.00036853,0.0002800467],"category_scores_gemma":[0.0002160452,0.0002001546,0.0002323495,0.0006005152,0.0004453064,0.0005073012,0.0003222491,0.0004891763,0.00006729901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001003112,"about_ca_system_score_gemma":0.0009187421,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05353472,"about_ca_topic_score_gemma":0.03386008,"domain_scores_codex":[0.9963,0.001252061,0.0004240305,0.0005609319,0.0003270826,0.001135936],"domain_scores_gemma":[0.9986417,0.000611254,0.0001486843,0.0001246132,0.0002363265,0.000237435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004180631,0.002496518,0.09363384,0.0005178635,0.000396942,0.0001309327,0.01768583,0.001153287,0.5608743,0.09820989,0.04707694,0.1774056],"study_design_scores_gemma":[0.0003341254,0.0004366351,0.8843688,0.0005644846,0.0000566681,0.0000167201,0.00529681,0.0009242491,0.03788597,0.04437311,0.02525826,0.0004841225],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9319808,0.004024506,0.002490398,0.04788361,0.0002026475,0.0005303914,0.00006391255,0.0002155012,0.01260818],"genre_scores_gemma":[0.9630778,0.0142396,0.00322962,0.001792083,0.0003965725,0.000161334,0.0002149607,0.000006710169,0.01688126],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.790735,"threshold_uncertainty_score":0.9837695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02907226209512157,"score_gpt":0.3121349374261747,"score_spread":0.2830626753310531,"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."}}