{"id":"W7017883944","doi":"","title":"Campylobactériose humaine et variations climatiques au Québec : a&#13;\\nnalyse de séries temporelles selon les modèles SARIMA et SARIMAX","year":2018,"lang":"fr","type":"other","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Population; Ectotherm; Margin (machine learning); Bioregion","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":[0.001401989,0.0004871361,0.0004302996,0.001378752,0.0007037252,0.001208219,0.001020882,0.0004438123,0.01134203],"category_scores_gemma":[0.003127214,0.0002263698,0.0007868955,0.002254306,0.0003821256,0.0004797388,0.0003973852,0.000763683,0.0008595835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01302451,"about_ca_system_score_gemma":0.01037655,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.989186,"about_ca_topic_score_gemma":0.9891059,"domain_scores_codex":[0.9995839,0.00007802328,0.00001783007,0.00008994601,0.0001232879,0.000106928],"domain_scores_gemma":[0.9986058,0.0003569314,0.0001463339,0.0001292228,0.0006514558,0.0001104209],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008173812,0.0001590402,0.7493024,0.0003329605,0.001092895,0.0005124137,0.001415933,0.07112222,0.001669443,0.01078192,0.05803424,0.1047592],"study_design_scores_gemma":[0.0000498808,0.00006423613,0.8798304,0.0001636902,0.0001497278,0.0001120434,0.001444796,0.08271681,0.001002088,0.0006833451,0.03372595,0.00005715938],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8817582,0.004333237,0.01132172,0.002040354,0.0002010737,0.0001214722,0.07317889,0.0009643854,0.02608071],"genre_scores_gemma":[0.9467164,0.00101649,0.004213703,0.0001090495,0.0000300837,0.00007644881,0.01430746,0.0001791206,0.03335122],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01302451,"threshold_uncertainty_score":0.09449989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01070508761262817,"score_gpt":0.2100679940091578,"score_spread":0.1993629063965296,"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."}}