{"id":"W4396536278","doi":"10.1515/9782760556645-fm","title":"Front Matter","year":2022,"lang":"fr","type":"paratext","venue":"Presses de l'Université du Québec eBooks","topic":"Information Technology and Learning","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bibliothèque et Archives nationales du Québec","funders":"","keywords":"Front (military); Geology; Oceanography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["insufficient_payload"],"domain":null,"study_design":"not_applicable","genre":"other","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["insufficient_payload"],"domain":null,"study_design":"not_applicable","genre":"other","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003533147,0.0003459012,0.00038779,0.0002448759,0.002378001,0.00009637057,0.001233349,0.0006295075,0.8175045],"category_scores_gemma":[0.00005563739,0.0004212716,0.0002388782,0.00009977861,0.0008610545,0.0002786489,0.0006519151,0.00142001,0.3390726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001340173,"about_ca_system_score_gemma":0.001499729,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.07271401,"about_ca_topic_score_gemma":0.0209971,"domain_scores_codex":[0.9977912,0.0004834072,0.000322074,0.0003641809,0.000370038,0.0006691492],"domain_scores_gemma":[0.9986432,0.0002800806,0.0004482701,0.0003608362,0.000111047,0.0001565761],"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":[0.00006547715,0.0000343898,0.006480744,0.0001388297,0.0001962247,0.00006198515,0.08407833,0.0006019144,0.00001327313,0.001617319,0.8795945,0.02711699],"study_design_scores_gemma":[0.0002968927,0.00005651716,0.0007402372,0.00005657967,0.0001467088,0.00002389701,0.01406531,0.0001449591,0.00006670003,0.0001185984,0.9838457,0.0004379528],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.02039427,0.002464755,0.001009103,0.00355171,0.001232587,0.0003251181,0.00005132844,0.000190538,0.9707806],"genre_scores_gemma":[0.1055023,0.000338799,0.0001729675,0.001600673,0.0003416,0.00003326069,0.00008507307,0.0000377487,0.8918876],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4784318,"threshold_uncertainty_score":0.9998239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007592776876239493,"score_gpt":0.2010970764423112,"score_spread":0.1935042995660717,"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."}}