{"id":"W2213409094","doi":"10.3917/i2d.153.0044","title":"Animer le réseau Must : un peu d’outils, beaucoup d’humain","year":2015,"lang":"fr","type":"article","venue":"I2D - Information données & documents","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Musée de la Civilisation","funders":"","keywords":"Humanities; Philosophy","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":[],"consensus_categories":[],"category_scores_codex":[0.003061364,0.0005701442,0.0002642998,0.001017944,0.007183031,0.008111865,0.001235264,0.00306284,0.01360658],"category_scores_gemma":[0.008011388,0.0003505763,0.0003338869,0.000966997,0.01028063,0.008507883,0.006378965,0.003341716,0.002632259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002202359,"about_ca_system_score_gemma":0.003261443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01001626,"about_ca_topic_score_gemma":0.01704847,"domain_scores_codex":[0.9977134,0.001168405,0.00005458755,0.0002226213,0.0006745707,0.0001663142],"domain_scores_gemma":[0.9966863,0.001439713,0.000171619,0.000485436,0.0006347972,0.0005821883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001102047,0.00005539724,0.001140534,0.0004476555,0.00002228634,0.001090192,0.196615,0.0005492063,0.005861001,0.4303063,0.2147944,0.1490078],"study_design_scores_gemma":[0.000005092842,0.00001851372,0.0004756633,0.0002598955,0.00000639406,0.0003688156,0.02467499,0.0004420784,0.0009248955,0.01714365,0.9556448,0.00003515731],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06783487,0.0116871,0.1497761,0.1631585,0.01101456,0.0002635988,0.0003430852,0.002056647,0.5938655],"genre_scores_gemma":[0.5097092,0.007328347,0.05812231,0.01559761,0.001784163,0.0002888139,0.0003721869,0.001780352,0.405017],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01360658,"threshold_uncertainty_score":0.04551852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2056089393041655,"score_gpt":0.3007754032526044,"score_spread":0.09516646394843889,"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."}}