{"id":"W7018394086","doi":"","title":"Description écologique des forêts du Québec /","year":2015,"lang":"fr","type":"other","venue":"Bibliothèque et Archives nationales du Québec (Québec government)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Set (abstract data type); Context (archaeology); Identification (biology); Relation (database)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006686227,0.001355925,0.0008906301,0.008066874,0.00328598,0.003828819,0.001308811,0.0008499325,0.09318697],"category_scores_gemma":[0.002180621,0.0005848776,0.0008935201,0.01549872,0.000694198,0.0008987409,0.0006810403,0.001584814,0.01628538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03070224,"about_ca_system_score_gemma":0.05146961,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9929732,"about_ca_topic_score_gemma":0.9933149,"domain_scores_codex":[0.9990858,0.00005660165,0.00005194748,0.0001487775,0.0004388956,0.0002179832],"domain_scores_gemma":[0.9979149,0.0001436591,0.0001509226,0.0001374882,0.001423138,0.0002299058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002515579,0.00007548766,0.02641169,0.001397874,0.0001613392,0.0004493644,0.001166036,0.003045757,0.001626971,0.02035244,0.8038266,0.1412349],"study_design_scores_gemma":[0.00003028309,0.00001120718,0.06230884,0.0003528071,0.00002404445,0.00009812536,0.0005223452,0.0007428151,0.0005070458,0.0003724433,0.9349805,0.00004965785],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.02008514,0.007000862,0.004204589,0.001897299,0.0005517835,0.0005793195,0.6883605,0.002545042,0.2747755],"genre_scores_gemma":[0.08855034,0.008708267,0.0106081,0.0006705734,0.0001431538,0.0007195064,0.3013426,0.001490917,0.5877666],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09318697,"threshold_uncertainty_score":0.3117415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01875702106733543,"score_gpt":0.2293929171796637,"score_spread":0.2106358961123283,"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."}}