{"id":"W2125696813","doi":"10.7202/1032719ar","title":"De l’imprimé vers l’électronique : réflexions et solutions techniques pour une édition savante en transition","year":2015,"lang":"fr","type":"article","venue":"Documentation et bibliothèques","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Humanities; Art; Philosophy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["scholarly_communication"],"domain":null,"study_design":"theoretical_or_conceptual","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"medium","status":"direct model label, unvalidated"},{"model":"gpt","categories":["scholarly_communication"],"domain":null,"study_design":"theoretical_or_conceptual","genre":"commentary","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","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0009892918,0.0003554391,0.0002614743,0.001320772,0.0002605114,0.01140977,0.0003236091,0.0002350958,0.0002373941],"category_scores_gemma":[0.0001395772,0.0003434494,0.0001705472,0.002958101,0.0001688939,0.04741737,0.0001054894,0.0003708232,0.0001659071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008553762,"about_ca_system_score_gemma":0.001212372,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006735623,"about_ca_topic_score_gemma":0.0007830061,"domain_scores_codex":[0.9971984,0.0006759678,0.0004768886,0.0004832463,0.0004977837,0.0006676996],"domain_scores_gemma":[0.998302,0.0002200653,0.000222752,0.0003228701,0.0004854423,0.0004468814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004330111,0.000335189,0.00001022693,0.00003580273,0.00005770793,0.00003482216,0.01581916,0.0006378243,0.01308587,0.8702785,0.08870903,0.01095258],"study_design_scores_gemma":[0.001196635,0.001218483,0.0009525903,0.0004535142,0.0001151844,0.0005014302,0.001553879,0.008676861,0.0580276,0.6451769,0.2812627,0.000864225],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00251427,0.002283908,0.756609,0.1497861,0.0005469569,0.0005356813,0.0001060728,0.0006528344,0.08696523],"genre_scores_gemma":[0.9121634,0.01488655,0.03763178,0.02022252,0.0004585589,0.0001438715,0.0005258287,0.0000615602,0.01390586],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9096492,"threshold_uncertainty_score":0.9999018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.157668042799947,"score_gpt":0.3785765046710211,"score_spread":0.2209084618710742,"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."}}