{"id":"W4399188229","doi":"10.1515/9782760557291-fm","title":"Front Matter","year":2022,"lang":"fr","type":"paratext","venue":"Presses de l'Université du Québec eBooks","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bibliothèque et Archives nationales du Québec","funders":"","keywords":"Front (military); Physics; Computer science; Meteorology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004921249,0.001644807,0.0009374227,0.001543786,0.002457379,0.005881763,0.001224179,0.003769904,0.9480664],"category_scores_gemma":[0.001496105,0.0005583171,0.0006457326,0.001106009,0.001037309,0.001566898,0.001676171,0.001701868,0.9130042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002017272,"about_ca_system_score_gemma":0.003248672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02634726,"about_ca_topic_score_gemma":0.03479854,"domain_scores_codex":[0.9995506,0.00002827674,0.00001307224,0.0001009838,0.00019355,0.0001134436],"domain_scores_gemma":[0.9988588,0.0001440506,0.0000483499,0.0001092667,0.0003987216,0.0004407373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006892219,0.00005124344,0.0001677663,0.0001434771,0.000006172217,0.00009037412,0.00004732942,0.00006060769,0.0005834349,0.002822643,0.9117038,0.08425422],"study_design_scores_gemma":[0.0000152753,0.00001189354,0.0004455317,0.00006518467,0.00000237422,0.00004450799,0.00004568154,0.00003491214,0.0001144646,0.0003048047,0.9989119,0.000003598115],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0004317694,0.0005935885,0.000185266,0.001719494,0.002050364,0.00004875329,0.00210373,0.000497726,0.9923693],"genre_scores_gemma":[0.0006157249,0.0001475781,0.00005234704,0.0002449145,0.0001140471,0.000007998159,0.0003103562,0.00005892264,0.9984481],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.05193359,"threshold_uncertainty_score":0.07407695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008701720270763724,"score_gpt":0.1880247232951251,"score_spread":0.1793230030243614,"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."}}