{"id":"W2345954532","doi":"10.4000/vertigo.17106","title":"Impact des feux sur la biomasse dans les savanes guinéo-soudaniennes du Togo","year":2016,"lang":"fr","type":"article","venue":"VertigO","topic":"African Botany and Ecology Studies","field":"Agricultural and Biological Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geography; Forestry","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000255492,0.0003519995,0.0003719711,0.0000215093,0.0007717934,0.00007038947,0.0003862958,0.0002907844,0.002059661],"category_scores_gemma":[0.0005327931,0.0001183551,0.0002943701,0.0003444297,0.001574368,0.000368333,0.0002298996,0.00008813974,0.0003969375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001432035,"about_ca_system_score_gemma":0.00002732489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001470252,"about_ca_topic_score_gemma":0.009192397,"domain_scores_codex":[0.9980146,0.0002623349,0.0003079967,0.0004668091,0.0001576007,0.0007906605],"domain_scores_gemma":[0.9982783,0.001139453,0.0001190488,0.0001144127,0.000128003,0.0002207867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005543601,0.0002294164,0.8383228,0.0000121723,0.0001258366,0.00006033136,0.0007023581,8.070108e-7,0.1076578,0.001469114,0.0143551,0.03700881],"study_design_scores_gemma":[0.00026394,0.0006622039,0.8580507,0.00009082101,0.00005867613,0.00007105208,0.001139095,0.000006488242,0.001312214,0.001616217,0.136392,0.0003365725],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9799221,0.005719708,0.00003506206,0.01055469,0.0006007822,0.00013287,0.000162802,0.0001060904,0.002765911],"genre_scores_gemma":[0.9760711,0.002473605,0.00009832616,0.0000873992,0.0006067475,0.0000161159,0.000004252185,0.000004342685,0.02063815],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1220369,"threshold_uncertainty_score":0.9988526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02411903345484566,"score_gpt":0.2289317917429489,"score_spread":0.2048127582881033,"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."}}