{"id":"W6981643787","doi":"","title":"Estimation de la xylogÃ©nÃ¨se chez l'Ã©pinette noire entre 1950 et 2010","year":2011,"lang":"fr","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Environmental factor; Statistical analysis; Coastal zone","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0002868658,0.0003074648,0.0002207922,0.001161192,0.0004419106,0.0007865019,0.0004229673,0.0003870547,0.002089747],"category_scores_gemma":[0.0007924704,0.0002201321,0.000508797,0.00120523,0.0002464927,0.0004298579,0.0004164615,0.0003959578,0.000498877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001589519,"about_ca_system_score_gemma":0.0009518457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3975838,"about_ca_topic_score_gemma":0.5846493,"domain_scores_codex":[0.999885,0.000006728018,0.00000587257,0.00004739522,0.00003700886,0.00001807172],"domain_scores_gemma":[0.9997533,0.00003760328,0.00004825264,0.00002491265,0.0001093879,0.00002649367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002296267,0.00003678749,0.914997,0.0001821456,0.0002174238,0.0005183126,0.002146704,0.01637213,0.0139648,0.001005844,0.003015064,0.04731404],"study_design_scores_gemma":[0.000002997975,0.00001082174,0.9881138,0.00002414568,0.00002268251,0.00002954688,0.0003990208,0.004732673,0.0005554035,0.00004458579,0.006052327,0.00001209789],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9842612,0.0005797153,0.001713173,0.00009466158,0.00002110627,0.00001473183,0.00495901,0.00009949612,0.008256952],"genre_scores_gemma":[0.9837936,0.0004670826,0.001919242,0.00002444748,0.00001623803,0.00002948429,0.007813953,0.00003256929,0.005903475],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3975838,"threshold_uncertainty_score":0.7905393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0063107809850872,"score_gpt":0.1370639999252878,"score_spread":0.1307532189402006,"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."}}