{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0007328076,0.000450126,0.0003901541,0.0001801927,0.000321895,0.002165533,0.0008115756,0.0004058778,0.0001165885],"category_scores_gemma":[0.0001676325,0.0003843313,0.000265235,0.001406532,0.0005852982,0.002431489,0.0002933618,0.0005467715,0.0002984199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001546263,"about_ca_system_score_gemma":0.0001783633,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02208529,"about_ca_topic_score_gemma":0.003101134,"domain_scores_codex":[0.996852,0.0001580526,0.0004656159,0.0005968588,0.0004347436,0.001492667],"domain_scores_gemma":[0.9978625,0.0003771267,0.0001864804,0.0006423446,0.0001875565,0.0007440359],"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":[0.00003851899,0.0004142712,0.003434531,0.0001358266,0.0001377626,0.005501529,0.009112152,0.0001084466,0.006608863,0.3093218,0.5739611,0.09122511],"study_design_scores_gemma":[0.0008126966,0.0002214602,0.03731187,0.0002744262,0.00006340359,0.00154896,0.0005137182,0.0007376513,0.006569675,0.01812817,0.9330055,0.0008125289],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2531323,0.01053342,0.02435154,0.03524574,0.0022883,0.0003269268,0.00004105665,0.0004157829,0.6736649],"genre_scores_gemma":[0.9144461,0.0002383813,0.004598998,0.01170507,0.001000317,0.000005447406,0.00001697639,0.00004301475,0.06794569],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6613138,"threshold_uncertainty_score":0.9998609,"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."}}