{"id":"W4392093524","doi":"10.7202/1113718ar","title":"Le patrimoine photographique dans le livre pour enfants : l’exemple de la collection « Révélateur »","year":2024,"lang":"fr","type":"article","venue":"Mémoires du livre","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Art; Humanities","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":[0.002738142,0.0005444156,0.0003272902,0.003526021,0.009030097,0.004972261,0.0007097969,0.001294601,0.02208728],"category_scores_gemma":[0.005263683,0.0002907388,0.0002729076,0.003484628,0.006096941,0.003037047,0.00475541,0.002241519,0.002635434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003939791,"about_ca_system_score_gemma":0.003455042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02203075,"about_ca_topic_score_gemma":0.09744103,"domain_scores_codex":[0.9980822,0.0007648369,0.00008439704,0.0002485582,0.0006038906,0.0002161178],"domain_scores_gemma":[0.9965112,0.001826841,0.0003219474,0.0004119546,0.0005925344,0.0003355395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002475515,0.00004634736,0.005856825,0.001595382,0.00001921419,0.005213862,0.6355145,0.0001192842,0.007257972,0.06676111,0.07370201,0.203666],"study_design_scores_gemma":[0.000004841525,0.00004563653,0.007847779,0.0005406289,0.000009457232,0.001648319,0.09274415,0.00002731683,0.001571739,0.001081037,0.8944563,0.00002278383],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3500651,0.0282636,0.01321799,0.02657136,0.005214538,0.0003250857,0.001441224,0.0004024116,0.5744988],"genre_scores_gemma":[0.6657006,0.01013934,0.00951636,0.002094849,0.001403263,0.0002095946,0.0005253195,0.0005444791,0.3098662],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02208728,"threshold_uncertainty_score":0.07388932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04082155914600335,"score_gpt":0.2726315079445555,"score_spread":0.2318099487985521,"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."}}