{"id":"W4411031528","doi":"10.7202/1116184ar","title":"Reboiser les terres dégradées pour augmenter les stocks de carbone et d’azote du sol et lutter contre les changements climatiques en Haïti","year":2024,"lang":"fr","type":"article","venue":"˜Le œclimatoscope","topic":"Agriculture and Rural Development Research","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Abitibi-Témiscamingue","funders":"","keywords":"Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0004815728,0.0006477494,0.000660421,0.0008305716,0.00133285,0.001528776,0.000638205,0.0006602951,0.005857103],"category_scores_gemma":[0.0003120557,0.0003028602,0.0008280133,0.0008332169,0.0004549608,0.0009862906,0.0005405234,0.001057462,0.001313544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001418313,"about_ca_system_score_gemma":0.001838882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03855793,"about_ca_topic_score_gemma":0.1412024,"domain_scores_codex":[0.9996879,0.00001857979,0.00001601089,0.00008630785,0.0001173843,0.00007383244],"domain_scores_gemma":[0.9996831,0.00002824596,0.00004047664,0.00002398322,0.0001688769,0.00005529863],"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":[0.000561398,0.0003330255,0.03645695,0.001810267,0.0001556502,0.0004424764,0.0007217071,0.002944903,0.8577137,0.000991615,0.001869506,0.09599881],"study_design_scores_gemma":[0.0001026642,0.002882053,0.361272,0.0005427341,0.0007278962,0.0007595153,0.004012511,0.01171284,0.4367782,0.001080112,0.1798748,0.0002546403],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9630026,0.007023271,0.006062455,0.0004071543,0.0001698843,0.0002137248,0.001700113,0.0003684886,0.0210523],"genre_scores_gemma":[0.9458037,0.005457061,0.01551322,0.0005390244,0.00004366834,0.0002744224,0.002875299,0.0002068157,0.02928685],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03855793,"threshold_uncertainty_score":0.07666695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02549934758310491,"score_gpt":0.2871364212290969,"score_spread":0.261637073645992,"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."}}