{"id":"W2012343963","doi":"10.4000/ocim.710","title":"« Ni vu, ni connu », une scénographie de camouflages","year":2007,"lang":"fr","type":"article","venue":"La Lettre de l’OCIM","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Musée de la Civilisation","funders":"","keywords":"Humanities; Art","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":[0.0006069347,0.0005636995,0.0003201689,0.002247005,0.004377891,0.005172938,0.000462056,0.001152565,0.008157352],"category_scores_gemma":[0.001716431,0.0002488552,0.000506438,0.002022336,0.004157092,0.00279703,0.002485438,0.001396414,0.0005897119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00321179,"about_ca_system_score_gemma":0.001782876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03364199,"about_ca_topic_score_gemma":0.06107752,"domain_scores_codex":[0.9995143,0.0002036012,0.000009703217,0.00007657397,0.0001093116,0.00008653267],"domain_scores_gemma":[0.9994061,0.0002818928,0.00005369884,0.00009035952,0.00008676118,0.0000811842],"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":[0.000356251,0.0000446139,0.0154996,0.001233735,0.00006718079,0.001917314,0.3470423,0.001986144,0.01549793,0.3655714,0.07150265,0.1792809],"study_design_scores_gemma":[0.0000106787,0.00008241252,0.0132842,0.0003544624,0.00002970349,0.001195086,0.07314672,0.0008244294,0.003812777,0.007764084,0.8994171,0.00007834102],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4099439,0.02399477,0.05285596,0.02237166,0.002566189,0.0001662467,0.001284201,0.001383621,0.4854335],"genre_scores_gemma":[0.8853434,0.006005832,0.01598968,0.00148627,0.0004845444,0.00009589939,0.0003313817,0.0004760219,0.08978689],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03364199,"threshold_uncertainty_score":0.06689233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09075810547081914,"score_gpt":0.3003055354773017,"score_spread":0.2095474300064826,"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."}}