{"id":"W4415464882","doi":"10.52358/mm.vi21.460","title":"EDI, l’apport caché des chaines éditoriales","year":2025,"lang":"fr","type":"article","venue":"Médiations et médiatisations","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Plank; Inclusion (mineral)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.01539556,0.0010278,0.000737888,0.009276993,0.005474407,0.01878842,0.001678505,0.003307052,0.03784326],"category_scores_gemma":[0.1153106,0.000643165,0.0007600141,0.005988687,0.006009301,0.01116303,0.004689328,0.003827939,0.008543632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005100024,"about_ca_system_score_gemma":0.01027225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002863235,"about_ca_topic_score_gemma":0.004791225,"domain_scores_codex":[0.9808387,0.00642543,0.001949419,0.001698349,0.008365329,0.0007228854],"domain_scores_gemma":[0.8757764,0.06957806,0.00916609,0.01022292,0.02931843,0.005938219],"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":[0.0001979425,0.00008001497,0.002063163,0.003431854,0.00006972683,0.000823381,0.01767195,0.0003840894,0.002577698,0.1890593,0.5824957,0.2011451],"study_design_scores_gemma":[0.000007190807,0.00002047599,0.0003727304,0.0006600217,0.00001703835,0.000212616,0.001533289,0.00009677742,0.0004008969,0.006658257,0.9900058,0.00001503956],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0161213,0.07112178,0.02976517,0.1441123,0.3037914,0.0005224237,0.001832139,0.001236923,0.4314965],"genre_scores_gemma":[0.21166,0.05746437,0.0399584,0.0319116,0.1524827,0.0008298116,0.001518113,0.00247024,0.5017047],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03784326,"threshold_uncertainty_score":0.1265983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1977260223526529,"score_gpt":0.34674491318223,"score_spread":0.1490188908295771,"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."}}