{"id":"W4411058597","doi":"10.54932/ouvl2258","title":"Comparaison des retombées économiques de la récolte de feuillus durs et de l’exploitation acéricole des érablières publiques au Québec","year":2025,"lang":"fr","type":"report","venue":"","topic":"Agroforestry and silvopastoral systems","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003463414,0.0007552238,0.00104113,0.0001106716,0.00124874,0.001015015,0.0008296717,0.001226208,0.0005863438],"category_scores_gemma":[0.001303464,0.0003878695,0.0005199731,0.0006128201,0.0013742,0.000883132,0.0002486055,0.0007101688,0.00003703829],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005501399,"about_ca_system_score_gemma":0.005058146,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7624879,"about_ca_topic_score_gemma":0.6420762,"domain_scores_codex":[0.9942548,0.00216428,0.001039115,0.0008466514,0.000351591,0.001343606],"domain_scores_gemma":[0.9957078,0.00236435,0.0006268598,0.0001914391,0.0005380671,0.00057153],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001484832,0.0003984495,0.9003073,0.0008233464,0.0002346848,0.00008406476,0.003310261,0.0004597405,0.005529791,0.02042301,0.01833889,0.04994196],"study_design_scores_gemma":[0.0001889102,0.0006280461,0.7046705,0.001344319,0.0001393613,0.000308458,0.003926832,0.0005253662,0.001792757,0.008245829,0.2774162,0.0008133531],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8783954,0.003876666,0.0004528256,0.003998937,0.0003866278,0.0006223619,0.00008462368,0.0003626205,0.1118199],"genre_scores_gemma":[0.8851546,0.003015697,0.001686817,0.0006891101,0.001123826,0.0002642063,0.0001971586,0.00001109045,0.1078575],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2590773,"threshold_uncertainty_score":0.9998573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05433976224513277,"score_gpt":0.3115486044295223,"score_spread":0.2572088421843895,"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."}}