{"id":"W2408020374","doi":"","title":"intelligentCAPTURE und dandelon.com: Collaborative Catalog Enrichment.","year":2007,"lang":"fr","type":"article","venue":"Ingénierie des systèmes d information","topic":"Library Science and Information Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.002585795,0.0004710086,0.000439599,0.0006983823,0.0007853891,0.002946469,0.001376134,0.0004087916,0.0001736951],"category_scores_gemma":[0.0002524359,0.0004535053,0.000148024,0.00347095,0.0005878974,0.05907399,0.0004204525,0.000390125,0.004020361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00068848,"about_ca_system_score_gemma":0.0007506583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000331907,"about_ca_topic_score_gemma":0.00004124662,"domain_scores_codex":[0.9955288,0.000158728,0.001952021,0.0003256103,0.0009997897,0.001035115],"domain_scores_gemma":[0.9963963,0.0002090251,0.001099925,0.0007429675,0.001119476,0.0004323304],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006582042,0.00009760599,0.00263863,0.0008105034,0.0001710506,0.00002832604,0.2532126,0.001218016,0.00005504875,0.2525149,0.05284219,0.4363454],"study_design_scores_gemma":[0.0006657694,0.0003651633,0.004001779,0.0005334753,0.00002143208,0.0002064474,0.0201822,0.03079808,0.004066249,0.005799184,0.9324989,0.0008612706],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008631038,0.00624801,0.8056737,0.001810796,0.008359582,0.001116235,0.000131145,0.0003465264,0.167683],"genre_scores_gemma":[0.9737618,0.0006431235,0.009552857,0.004329771,0.0006352852,0.00005385988,0.0005525029,0.00002572635,0.01044509],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9651307,"threshold_uncertainty_score":0.9997917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02161900196044591,"score_gpt":0.2599283873756957,"score_spread":0.2383093854152498,"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."}}