{"id":"W4413678915","doi":"10.7202/1119067ar","title":"Intelligence artificielle générative et usages scientifiques : les bibliothèques face à une littératie post-informationnelle","year":2025,"lang":"fr","type":"article","venue":"Documentation et bibliothèques","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Philosophy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","bibliometrics","scholarly_communication","insufficient_payload"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.001137367,0.0006279197,0.0005011701,0.006434015,0.0008185693,0.06710829,0.0009733309,0.0002581066,0.001942818],"category_scores_gemma":[0.0004900683,0.0005474155,0.0002508241,0.02155296,0.0006909673,0.1059241,0.0006345147,0.0004594704,0.0003437404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002296118,"about_ca_system_score_gemma":0.0008149816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006392711,"about_ca_topic_score_gemma":0.002250274,"domain_scores_codex":[0.9957243,0.0005575306,0.001222106,0.0008944906,0.0008413227,0.0007602394],"domain_scores_gemma":[0.9959947,0.0007888014,0.0005482115,0.0006976029,0.001668214,0.0003024535],"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":[0.00003707651,0.0003543918,0.0001559873,0.0002671397,0.0001118457,0.00001660077,0.03260263,0.002428774,0.00207808,0.8764266,0.05586054,0.02966037],"study_design_scores_gemma":[0.0008616771,0.001142169,0.005501951,0.002811971,0.0001346349,0.00006795085,0.02613629,0.03964101,0.2655998,0.2598186,0.3962973,0.001986631],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01007396,0.02578007,0.6644151,0.0529543,0.002155194,0.001015242,0.0001469977,0.0005320029,0.2429272],"genre_scores_gemma":[0.641057,0.03057558,0.01006809,0.01288528,0.0001421205,0.0001014967,0.0002983382,0.0000409403,0.3048311],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6543469,"threshold_uncertainty_score":0.9996977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1292857666821654,"score_gpt":0.3777998352281781,"score_spread":0.2485140685460127,"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."}}