{"id":"W4410572494","doi":"10.55790/journals/ressi.2015.e1609","title":"Compte-rendu du CERN Workshop on Innovations in Scholarly Communication (OAI9), 17-19 juin 2015, Genève","year":2015,"lang":"fr","type":"article","venue":"Revue électronique suisse de science de l information (RESSI)","topic":"Research Data Management Practices","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bibliothèque et Archives nationales du Québec","funders":"","keywords":"Large Hadron Collider; Political science; Physics; Nuclear physics","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01224255,0.001673551,0.001789979,0.003425998,0.002656309,0.009202177,0.002127085,0.002682721,0.1599507],"category_scores_gemma":[0.01089224,0.0005209987,0.0009900348,0.002437375,0.001759967,0.004637955,0.007116474,0.002318182,0.08122658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004133114,"about_ca_system_score_gemma":0.006573479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0138105,"about_ca_topic_score_gemma":0.02411762,"domain_scores_codex":[0.9932334,0.002243206,0.0002473151,0.0009845357,0.002317481,0.0009739698],"domain_scores_gemma":[0.9921896,0.001765335,0.0002765257,0.001585669,0.00213261,0.00205026],"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":[0.001094094,0.0001810511,0.001244483,0.0004557144,0.00006801314,0.0001991008,0.0005324022,0.001468583,0.00245033,0.03208079,0.8017976,0.158428],"study_design_scores_gemma":[0.0001093364,0.00008643554,0.002440613,0.0003229553,0.00001658771,0.0001219357,0.0003604181,0.00144751,0.002304711,0.008482478,0.9842739,0.00003319094],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.03592104,0.09053145,0.121421,0.08524448,0.07890468,0.001448356,0.04333185,0.01656871,0.5266285],"genre_scores_gemma":[0.1026698,0.02520011,0.07614256,0.002666679,0.01101016,0.0009931423,0.04272934,0.009752176,0.7288359],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9907978,"threshold_uncertainty_score":0.5350884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1220177777391909,"score_gpt":0.3789545999164228,"score_spread":0.2569368221772318,"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."}}